Psych 251 PS2: Tidying Data
Andrew Lampinen
September 27, 2018
In this assignment we’ll learn about dplyr and
tidyr, two packages from the tidyverse that
allow elegant and easily understandable data tidying and manipulation.
We’ll do this by working through the steps of loading an actual dataset,
tidying it up, and carrying out some basic analyses.
The dataset we’re using comes from the OSF Reproduciblity project replication of a study by Maya Tamir, Christopher Mitchell, and our very own James Gross (“Hedonic and Instrumental Motives in Anger Regulation,” Tamir, Mitchell, and Gross, Psychological Science, 2008). You can find the replication report here, and the original paper here. The replication tests two hypotheses from the original paper:
Rating hypothesis: Participants will prefer listening to angry music (or recalling an anger-inducing experience) before playing a confrontational (violent) game, but will prefer listening to exciting or neutral music (or recalling a calm experience) before a neutral game. This is assessed through preference ratings where the participants read a description of a game, and then are asked to rate on a likert scale.
Performance hypothesis: Subjects would perform better after listening to angry music on a confrontational game (not one of the ones described in the materials for the previous hypothesis, to avoid contamination), but would perform better on a non-confrontational game (again, not described in the materials for hypothesis 1) after listening to non-angry music. This is computed by having the subjects play without music for 5 minutes, and then after/with music for 5 minutes, and comparing change scores depending on the music type.
First, let’s load the libraries we’re going to use.
library(foreign) # for reading spss formatted data
library(tidyr)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(stringr) # useful for some string manipulation
library(ggplot2)Load Data
d = read.spss("data/Tamiretal2008ReplicationData.sav", to.data.frame=T)Take a look at the data structure:
head(d)## Subject Cond Exper
## 1 1 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 2 2 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 3 3 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 4 4 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 5 5 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 6 6 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## Inifile Date Time Game1Angry1 Game1Angry2 Game1Angry3
## 1 default.mlp 13642819200 40781 6 6 5
## 2 default.mlp 13642819200 50753 7 7 7
## 3 default.mlp 13642819200 54540 6 5 7
## 4 default.mlp 13642905600 34952 4 1 1
## 5 default.mlp 13642905600 49095 6 6 7
## 6 default.mlp 13642905600 59714 5 5 6
## Game1AngryFriends Game1AngryStrangers Game1CalmFriends Game1CalmStrangers
## 1 2 5 2 2
## 2 7 7 6 6
## 3 2 2 2 2
## 4 6 6 2 1
## 5 6 6 2 2
## 6 3 4 5 4
## Game1ExcitedFriends Game1ExcitedStrangers Game1Exciting1 Game1Exciting2
## 1 1 2 3 2
## 2 6 6 5 3
## 3 2 2 2 3
## 4 3 4 5 4
## 5 5 5 1 3
## 6 6 4 3 2
## Game1Exciting3 Game1Intro Game1Neutral1 Game1Neutral2 Game1Neutral3
## 1 6 ok 2 4 4
## 2 2 ok 1 1 1
## 3 4 ok 1 2 3
## 4 5 ok 1 2 2
## 5 2 ok 3 2 4
## 6 4 ok 2 2 4
## Game2Angry1 Game2Angry2 Game2Angry3 Game2AngryFriends Game2AngryStrangers
## 1 6 4 6 3 6
## 2 7 6 7 6 7
## 3 5 3 6 3 3
## 4 6 2 6 3 6
## 5 5 6 6 5 6
## 6 6 5 6 3 5
## Game2CalmFriends Game2CalmStrangers Game2ExcitedFriends Game2ExcitedStrangers
## 1 1 2 1 1
## 2 2 3 5 5
## 3 3 3 3 3
## 4 1 1 2 4
## 5 1 1 4 4
## 6 3 2 5 4
## Game2Exciting1 Game2Exciting2 Game2Exciting3 Game2Intro Game2Neutral1
## 1 3 2 4 ok 1
## 2 5 2 1 ok 1
## 3 2 5 2 ok 4
## 4 3 2 2 ok 1
## 5 1 2 2 ok 4
## 6 2 2 3 ok 2
## Game2Neutral2 Game2Neutral3 Game3Angry1 Game3Angry2 Game3Angry3
## 1 3 1 2 2 3
## 2 1 2 6 3 5
## 3 3 1 2 2 3
## 4 1 3 2 1 6
## 5 4 5 3 5 6
## 6 3 4 2 2 5
## Game3AngryFriends Game3AngryStrangers Game3CalmFriends Game3CalmStrangers
## 1 3 2 7 6
## 2 3 2 6 5
## 3 4 4 3 3
## 4 5 4 2 2
## 5 1 3 5 5
## 6 1 1 4 3
## Game3ExcitedFriends Game3ExcitedStrangers Game3Exciting1 Game3Exciting2
## 1 6 5 2 2
## 2 6 5 4 3
## 3 4 4 3 6
## 4 5 6 3 1
## 5 6 5 3 1
## 6 4 2 1 2
## Game3Exciting3 Game3Intro Game3Neutral1 Game3Neutral2 Game3Neutral3
## 1 3 ok 5 6 5
## 2 3 ok 2 1 5
## 3 2 ok 2 3 3
## 4 3 ok 2 2 6
## 5 3 ok 2 4 5
## 6 2 ok 5 4 4
## Game4Angry1 Game4Angry2 Game4Angry3 Game4AngryFriends Game4AngryStrangers
## 1 2 2 2 2 2
## 2 2 5 2 4 4
## 3 5 2 2 4 5
## 4 1 1 2 1 1
## 5 3 4 3 2 3
## 6 2 3 3 1 2
## Game4CalmFriends Game4CalmStrangers Game4ExcitedFriends Game4ExcitedStrangers
## 1 5 5 7 4
## 2 2 4 3 4
## 3 2 4 4 5
## 4 2 2 4 4
## 5 5 5 5 6
## 6 4 4 5 4
## Game4Exciting1 Game4Exciting2 Game4Exciting3 Game4Intro Game4Neutral1
## 1 5 5 2 ok 1
## 2 1 2 6 ok 5
## 3 7 4 5 ok 3
## 4 6 6 6 ok 4
## 5 1 5 5 ok 4
## 6 2 4 3 ok 3
## Game4Neutral2 Game4Neutral3 MusicSelectionEnd MusicSelectionInstrx
## 1 5 2 ok ok
## 2 5 2 ok ok
## 3 2 4 ok ok
## 4 5 2 ok ok
## 5 2 5 ok ok
## 6 5 5 ok ok
## RecallSelectionEnd RecallSelectionInstrx Subject2 Cond2
## 1 ok ok 1 2
## 2 ok ok 2 3
## 3 ok ok 3 1
## 4 ok ok 4 4
## 5 ok ok 5 5
## 6 ok ok 6 6
## Exper_A Inifile_A
## 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## Date_A Time_A DescribeMusic HowActiveAngry1 HowActiveAngry2
## 1 13642819200 43151 2 4 4
## 2 13642819200 53012 3 5 5
## 3 13642819200 57041 2 4 4
## 4 13642905600 37630 3 5 3
## 5 13642905600 51434 2 5 4
## 6 13642905600 62320 3 3 3
## HowActiveAngry3 HowActiveExciting1 HowActiveExciting2 HowActiveExciting3
## 1 4 5 4 5
## 2 5 5 2 4
## 3 4 2 1 3
## 4 3 5 5 5
## 5 5 3 3 3
## 6 2 3 3 4
## HowActiveNeutral1 HowActiveNeutral2 HowActiveNeutral3 HowAngryAngry1
## 1 2 2 2 5
## 2 2 2 1 5
## 3 1 2 1 4
## 4 2 2 1 3
## 5 2 1 1 2
## 6 1 2 1 2
## HowAngryAngry2 HowAngryAngry3 HowAngryExciting1 HowAngryExciting2
## 1 4 4 3 4
## 2 5 5 4 3
## 3 4 4 3 1
## 4 2 3 1 1
## 5 2 3 2 2
## 6 2 2 2 1
## HowAngryExciting3 HowAngryNeutral1 HowAngryNeutral2 HowAngryNeutral3
## 1 3 2 2 1
## 2 3 2 1 1
## 3 3 1 1 2
## 4 1 2 1 1
## 5 1 1 1 1
## 6 1 1 1 1
## HowExcitedAngry1 HowExcitedAngry2 HowExcitedAngry3 HowExcitedExciting1
## 1 4 3 3 4
## 2 5 5 5 4
## 3 3 3 2 2
## 4 4 1 3 4
## 5 4 4 5 3
## 6 5 2 3 3
## HowExcitedExciting2 HowExcitedExciting3 HowExcitedNeutral1 HowExcitedNeutral2
## 1 4 4 2 2
## 2 2 4 3 2
## 3 2 3 2 1
## 4 3 5 2 2
## 5 3 3 2 1
## 6 2 4 1 1
## HowExcitedNeutral3 HowPleasantAngry1 HowPleasantAngry2 HowPleasantAngry3
## 1 2 1 2 1
## 2 1 1 2 1
## 3 2 2 2 4
## 4 1 1 1 3
## 5 3 4 3 2
## 6 2 2 2 3
## HowPleasantExciting1 HowPleasantExciting2 HowPleasantExciting3
## 1 2 2 1
## 2 1 4 3
## 3 2 2 2
## 4 4 4 3
## 5 1 1 2
## 6 3 3 4
## HowPleasantNeutral1 HowPleasantNeutral2 HowPleasantNeutral3 MusicRatingEnd
## 1 5 4 5 ok
## 2 4 4 4 ok
## 3 2 2 1 ok
## 4 2 4 5 ok
## 5 1 1 5 ok
## 6 3 3 4 ok
## MusicRatingInstrx WhichGames aboutyou age distractions endinstructions
## 1 ok ok ok 18 ok ok
## 2 ok ok ok 20 ok ok
## 3 ok ok ok 18 ok ok
## 4 ok ok ok 18 ok ok
## 5 ok ok ok 18 ok ok
## 6 ok ok ok 19 ok ok
## ethnicity overlooking race sex whatabout year Subject3 DDNoMusicLevel
## 1 2 ok 2 1 ok 1 1 3
## 2 2 ok 2 2 ok 2 2 3
## 3 2 ok 2 1 ok 1 3 2
## 4 2 ok 2 1 ok 1 4 3
## 5 2 ok 2 1 ok 1 5 3
## 6 2 ok 2 1 ok 1 6 3
## DDNoMusicScore DDMusicLevel DDMusicScore SOFNoMusicEnemies
## 1 0 3 830 22
## 2 20 3 2930 18
## 3 1250 3 370 15
## 4 1742 3 1921 3
## 5 60 3 1750 18
## 6 840 3 1380 23
## SOFNoMusicFriendlies SOFNoMusicTime SOFMusicEnemies SOFMusicFriendlies
## 1 2 24360 19 0
## 2 1 23580 18 2
## 3 0 15300 23 1
## 4 0 5280 19 0
## 5 2 19140 23 3
## 6 1 23220 24 0
## SOFMusicTime GameComments
## 1 23340
## 2 22500
## 3 24300
## 4 16860 Participant died, restart
## 5 20820 Error in game towards the end of time
## 6 23400
## DoNotUseVideoGamePerformanceData ConfrontationalAngryMusicScore
## 1 NA 5.500000
## 2 NA 6.833333
## 3 NA 5.333333
## 4 1 3.333333
## 5 1 6.000000
## 6 NA 5.500000
## ConfrontationalExcitingMusicScore ConfrontationalNeutralMusicScore
## 1 3.333333 2.500000
## 2 3.000000 1.166667
## 3 3.000000 2.333333
## 4 3.500000 1.666667
## 5 1.833333 3.666667
## 6 2.666667 2.833333
## ConfrontationalAngryRecallScore ConfrontationalExcitingRecallScore
## 1 3.75 1.25
## 2 7.00 5.75
## 3 2.25 2.25
## 4 6.00 3.50
## 5 6.00 4.75
## 6 3.75 5.00
## ConfrontationalNeutralRecallScore NonconfrontationalAngryMusicScore
## 1 2.00 2.166667
## 2 5.25 3.833333
## 3 2.25 2.666667
## 4 1.50 2.166667
## 5 1.75 4.000000
## 6 4.00 2.833333
## NonconfrontationalExcitingMusicScore NonconfrontationalNeutralMusicScore
## 1 3.166667 4.000000
## 2 3.166667 3.333333
## 3 4.500000 2.833333
## 4 4.166667 3.500000
## 5 3.000000 3.666667
## 6 2.333333 4.333333
## NonconfrontationalAngryRecallScore NonconfrontationalExcitingRecallScore
## 1 2.50 5.25
## 2 3.00 5.25
## 3 4.25 4.25
## 4 3.75 5.00
## 5 2.00 5.75
## 6 1.25 3.50
## NonconfrontationalNeutralRecallScore ConfrontationalAngerScore
## 1 6.25 4.8
## 2 5.25 6.9
## 3 3.25 4.1
## 4 2.00 4.4
## 5 5.00 6.0
## 6 3.75 4.8
## ConfrontationalExcitingScore ConfrontationalNeutralScore
## 1 2.5 2.3
## 2 4.1 2.8
## 3 2.7 2.3
## 4 3.5 1.6
## 5 3.0 2.9
## 6 3.6 3.3
## NonconfrontationalAngerScore NonconfrontationalExcitingScore
## 1 2.3 4.0
## 2 3.5 4.0
## 3 3.3 4.4
## 4 2.8 4.5
## 5 3.2 4.1
## 6 2.2 2.8
## NonconfrontationalNeutralScore Usable DoNotUse
## 1 4.9 1 NA
## 2 4.1 0 1
## 3 3.0 1 NA
## 4 2.9 1 NA
## 5 4.2 1 NA
## 6 4.1 1 NA
## ProblemDetails
## 1
## 2 Female participant (this is a males only study)
## 3
## 4
## 5
## 6
## DinerDashWithMusicScore DinerDashWithoutMusicScore MusicCondition
## 1 5830 5000 Exciting
## 2 7930 5020 Neutral
## 3 5370 1250 Anger
## 4 6921 6742 Anger
## 5 6750 5060 Exciting
## 6 6380 5840 Neutral
## ZDinerDashWithMusicScore ZDinerDashWithoutMusicScore ZSOFNoMusicEnemies
## 1 -0.07333283 0.2692740 0.7501199
## 2 NA NA NA
## 3 -0.73344247 -2.8616517 -0.1401958
## 4 1.49227504 1.7236934 -1.6664514
## 5 1.24688645 0.3193688 0.2413681
## 6 0.71592870 0.9706014 0.8773079
## ZSOFMusicEnemies DinerDashDifferenceScore SOFDifferenceScore
## 1 -0.2020329 -0.3426068 -0.95215278
## 2 NA NA NA
## 3 0.3183548 2.1282092 0.45855062
## 4 -0.2020329 -0.2314183 1.46441854
## 5 0.3183548 0.9275176 0.07698673
## 6 0.4484517 -0.2546727 -0.42885618
## PleasantScoreForAngryMusic PleasantScoreForExcitingMusic
## 1 1.333333 1.666667
## 2 1.333333 2.666667
## 3 2.666667 2.000000
## 4 1.666667 3.666667
## 5 3.000000 1.333333
## 6 2.333333 3.333333
## PleasantScoreForNeutralMusic AngryScoreForAngryMusic
## 1 4.666667 4.333333
## 2 4.000000 5.000000
## 3 1.666667 4.000000
## 4 3.666667 2.666667
## 5 2.333333 2.333333
## 6 3.333333 2.000000
## AngryScoreForExcitingMusic AngryScoreForNeutralMusic
## 1 3.333333 1.666667
## 2 3.333333 1.333333
## 3 2.333333 1.333333
## 4 1.000000 1.333333
## 5 1.666667 1.000000
## 6 1.333333 1.000000
## ExcitedScoreForExcitingMusic ExcitedScoreForNeutralMusic
## 1 4.000000 2.000000
## 2 3.333333 2.000000
## 3 2.333333 1.666667
## 4 4.000000 1.666667
## 5 3.000000 2.000000
## 6 3.000000 1.333333
## ActiveScoreForExcitingMusic ActiveScoreForNeutralMusic
## 1 4.666667 2.000000
## 2 3.666667 1.666667
## 3 2.000000 1.333333
## 4 5.000000 1.666667
## 5 3.000000 1.333333
## 6 3.333333 1.333333
## ExcitedScoreForAngryMusic ActiveScoreForAngryMusic
## 1 3.333333 4.000000
## 2 5.000000 5.000000
## 3 2.666667 4.000000
## 4 2.666667 3.666667
## 5 4.333333 4.666667
## 6 3.333333 2.666667This data is what we call wide form – each subject is a single row, and the columns represent different observations. This is a somewhat inconvenient way of representing the data, for example if we wanted to do the same operation to each likert rating (for example normalize it to be in the range 0-1), we’d have to do it on each of the 40 or so rating columns. To avoid this, our eventual goal will be to convert the data into long form, where each row is a single observation.
For now, take a look at the column names to get a better idea of what all is in the dataset.
colnames(d)## [1] "Subject"
## [2] "Cond"
## [3] "Exper"
## [4] "Inifile"
## [5] "Date"
## [6] "Time"
## [7] "Game1Angry1"
## [8] "Game1Angry2"
## [9] "Game1Angry3"
## [10] "Game1AngryFriends"
## [11] "Game1AngryStrangers"
## [12] "Game1CalmFriends"
## [13] "Game1CalmStrangers"
## [14] "Game1ExcitedFriends"
## [15] "Game1ExcitedStrangers"
## [16] "Game1Exciting1"
## [17] "Game1Exciting2"
## [18] "Game1Exciting3"
## [19] "Game1Intro"
## [20] "Game1Neutral1"
## [21] "Game1Neutral2"
## [22] "Game1Neutral3"
## [23] "Game2Angry1"
## [24] "Game2Angry2"
## [25] "Game2Angry3"
## [26] "Game2AngryFriends"
## [27] "Game2AngryStrangers"
## [28] "Game2CalmFriends"
## [29] "Game2CalmStrangers"
## [30] "Game2ExcitedFriends"
## [31] "Game2ExcitedStrangers"
## [32] "Game2Exciting1"
## [33] "Game2Exciting2"
## [34] "Game2Exciting3"
## [35] "Game2Intro"
## [36] "Game2Neutral1"
## [37] "Game2Neutral2"
## [38] "Game2Neutral3"
## [39] "Game3Angry1"
## [40] "Game3Angry2"
## [41] "Game3Angry3"
## [42] "Game3AngryFriends"
## [43] "Game3AngryStrangers"
## [44] "Game3CalmFriends"
## [45] "Game3CalmStrangers"
## [46] "Game3ExcitedFriends"
## [47] "Game3ExcitedStrangers"
## [48] "Game3Exciting1"
## [49] "Game3Exciting2"
## [50] "Game3Exciting3"
## [51] "Game3Intro"
## [52] "Game3Neutral1"
## [53] "Game3Neutral2"
## [54] "Game3Neutral3"
## [55] "Game4Angry1"
## [56] "Game4Angry2"
## [57] "Game4Angry3"
## [58] "Game4AngryFriends"
## [59] "Game4AngryStrangers"
## [60] "Game4CalmFriends"
## [61] "Game4CalmStrangers"
## [62] "Game4ExcitedFriends"
## [63] "Game4ExcitedStrangers"
## [64] "Game4Exciting1"
## [65] "Game4Exciting2"
## [66] "Game4Exciting3"
## [67] "Game4Intro"
## [68] "Game4Neutral1"
## [69] "Game4Neutral2"
## [70] "Game4Neutral3"
## [71] "MusicSelectionEnd"
## [72] "MusicSelectionInstrx"
## [73] "RecallSelectionEnd"
## [74] "RecallSelectionInstrx"
## [75] "Subject2"
## [76] "Cond2"
## [77] "Exper_A"
## [78] "Inifile_A"
## [79] "Date_A"
## [80] "Time_A"
## [81] "DescribeMusic"
## [82] "HowActiveAngry1"
## [83] "HowActiveAngry2"
## [84] "HowActiveAngry3"
## [85] "HowActiveExciting1"
## [86] "HowActiveExciting2"
## [87] "HowActiveExciting3"
## [88] "HowActiveNeutral1"
## [89] "HowActiveNeutral2"
## [90] "HowActiveNeutral3"
## [91] "HowAngryAngry1"
## [92] "HowAngryAngry2"
## [93] "HowAngryAngry3"
## [94] "HowAngryExciting1"
## [95] "HowAngryExciting2"
## [96] "HowAngryExciting3"
## [97] "HowAngryNeutral1"
## [98] "HowAngryNeutral2"
## [99] "HowAngryNeutral3"
## [100] "HowExcitedAngry1"
## [101] "HowExcitedAngry2"
## [102] "HowExcitedAngry3"
## [103] "HowExcitedExciting1"
## [104] "HowExcitedExciting2"
## [105] "HowExcitedExciting3"
## [106] "HowExcitedNeutral1"
## [107] "HowExcitedNeutral2"
## [108] "HowExcitedNeutral3"
## [109] "HowPleasantAngry1"
## [110] "HowPleasantAngry2"
## [111] "HowPleasantAngry3"
## [112] "HowPleasantExciting1"
## [113] "HowPleasantExciting2"
## [114] "HowPleasantExciting3"
## [115] "HowPleasantNeutral1"
## [116] "HowPleasantNeutral2"
## [117] "HowPleasantNeutral3"
## [118] "MusicRatingEnd"
## [119] "MusicRatingInstrx"
## [120] "WhichGames"
## [121] "aboutyou"
## [122] "age"
## [123] "distractions"
## [124] "endinstructions"
## [125] "ethnicity"
## [126] "overlooking"
## [127] "race"
## [128] "sex"
## [129] "whatabout"
## [130] "year"
## [131] "Subject3"
## [132] "DDNoMusicLevel"
## [133] "DDNoMusicScore"
## [134] "DDMusicLevel"
## [135] "DDMusicScore"
## [136] "SOFNoMusicEnemies"
## [137] "SOFNoMusicFriendlies"
## [138] "SOFNoMusicTime"
## [139] "SOFMusicEnemies"
## [140] "SOFMusicFriendlies"
## [141] "SOFMusicTime"
## [142] "GameComments"
## [143] "DoNotUseVideoGamePerformanceData"
## [144] "ConfrontationalAngryMusicScore"
## [145] "ConfrontationalExcitingMusicScore"
## [146] "ConfrontationalNeutralMusicScore"
## [147] "ConfrontationalAngryRecallScore"
## [148] "ConfrontationalExcitingRecallScore"
## [149] "ConfrontationalNeutralRecallScore"
## [150] "NonconfrontationalAngryMusicScore"
## [151] "NonconfrontationalExcitingMusicScore"
## [152] "NonconfrontationalNeutralMusicScore"
## [153] "NonconfrontationalAngryRecallScore"
## [154] "NonconfrontationalExcitingRecallScore"
## [155] "NonconfrontationalNeutralRecallScore"
## [156] "ConfrontationalAngerScore"
## [157] "ConfrontationalExcitingScore"
## [158] "ConfrontationalNeutralScore"
## [159] "NonconfrontationalAngerScore"
## [160] "NonconfrontationalExcitingScore"
## [161] "NonconfrontationalNeutralScore"
## [162] "Usable"
## [163] "DoNotUse"
## [164] "ProblemDetails"
## [165] "DinerDashWithMusicScore"
## [166] "DinerDashWithoutMusicScore"
## [167] "MusicCondition"
## [168] "ZDinerDashWithMusicScore"
## [169] "ZDinerDashWithoutMusicScore"
## [170] "ZSOFNoMusicEnemies"
## [171] "ZSOFMusicEnemies"
## [172] "DinerDashDifferenceScore"
## [173] "SOFDifferenceScore"
## [174] "PleasantScoreForAngryMusic"
## [175] "PleasantScoreForExcitingMusic"
## [176] "PleasantScoreForNeutralMusic"
## [177] "AngryScoreForAngryMusic"
## [178] "AngryScoreForExcitingMusic"
## [179] "AngryScoreForNeutralMusic"
## [180] "ExcitedScoreForExcitingMusic"
## [181] "ExcitedScoreForNeutralMusic"
## [182] "ActiveScoreForExcitingMusic"
## [183] "ActiveScoreForNeutralMusic"
## [184] "ExcitedScoreForAngryMusic"
## [185] "ActiveScoreForAngryMusic"And see if you can figure out what range the likert scores are in.
What’s the highest number on the likert scale, and what’s the lowest?
(Hint, d$Game1Angry1 is one of the likert rating columns,
and you may want to use unique or range or
hist)
show(d$Game1Angry1)## [1] 6 7 6 4 6 5 6 5 4 7 3 5 4 2 6 4 3 7 7 5 4 4 5 4 6
## [26] 4 7 6 1 3 5 7 4 2 6 4 1 3 5 6 6 5 5 5 1 4 3 5 6 7
## [51] 5 7 3 7 3 3 5 7 6 7 6 6 6 7 7 1 6 7 5 6 1 3 4 6 6
## [76] 6 7 3 5 5 6 7 7 2 4 1 7 7 5 NA NAHighest number: [7] Lowest number: [1]
cleaning up a bit
First, we’ll get rid of rows and columns of the data that we don’t need.
filter out excluded rows
First, we need to filter out any rows that should be
excluded. According to the report, there are two exclusions:
“exclude data from participant 2 and participant 23 participant 2 is female, and this is a males only study participant 23 was set up on part 2 of the study (the music ratings) twice and never did part 1”
You can see participant 23’s data and the fact that they did not do part 1 by looking at the last rows of the dataframe:
tail(d)## Subject Cond Exper
## 86 87 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 87 88 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 88 89 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 89 90 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 90 23 NA
## 91 23 NA
## Inifile Date Time Game1Angry1 Game1Angry2 Game1Angry3
## 86 default.mlp 13644633600 40065 1 3 4
## 87 default.mlp 13644633600 51237 7 7 5
## 88 default.mlp 13644633600 54293 7 6 6
## 89 default.mlp 13644633600 58190 5 5 5
## 90 NA NA NA NA NA
## 91 NA NA NA NA NA
## Game1AngryFriends Game1AngryStrangers Game1CalmFriends Game1CalmStrangers
## 86 6 7 1 1
## 87 4 1 4 4
## 88 7 5 3 2
## 89 7 7 1 1
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game1ExcitedFriends Game1ExcitedStrangers Game1Exciting1 Game1Exciting2
## 86 1 1 1 1
## 87 7 4 7 7
## 88 7 6 3 5
## 89 4 1 1 1
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game1Exciting3 Game1Intro Game1Neutral1 Game1Neutral2 Game1Neutral3
## 86 1 ok 2 2 3
## 87 6 ok 2 1 1
## 88 2 ok 1 2 1
## 89 1 ok 1 1 6
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game2Angry1 Game2Angry2 Game2Angry3 Game2AngryFriends Game2AngryStrangers
## 86 5 5 7 1 7
## 87 7 7 4 1 1
## 88 6 4 6 7 2
## 89 5 1 7 7 7
## 90 NA NA NA NA NA
## 91 NA NA NA NA NA
## Game2CalmFriends Game2CalmStrangers Game2ExcitedFriends
## 86 4 4 2
## 87 5 6 7
## 88 3 1 7
## 89 1 1 1
## 90 NA NA NA
## 91 NA NA NA
## Game2ExcitedStrangers Game2Exciting1 Game2Exciting2 Game2Exciting3
## 86 2 5 1 1
## 87 4 7 1 1
## 88 5 1 3 1
## 89 4 3 2 2
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game2Intro Game2Neutral1 Game2Neutral2 Game2Neutral3 Game3Angry1 Game3Angry2
## 86 ok 1 1 1 5 3
## 87 ok 1 1 1 2 1
## 88 ok 1 2 2 2 4
## 89 ok 1 3 1 1 1
## 90 NA NA NA NA NA
## 91 NA NA NA NA NA
## Game3Angry3 Game3AngryFriends Game3AngryStrangers Game3CalmFriends
## 86 6 1 2 5
## 87 7 1 1 7
## 88 4 1 1 6
## 89 5 2 2 7
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game3CalmStrangers Game3ExcitedFriends Game3ExcitedStrangers Game3Exciting1
## 86 6 4 2 1
## 87 2 7 3 2
## 88 4 3 6 5
## 89 6 7 7 2
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game3Exciting2 Game3Exciting3 Game3Intro Game3Neutral1 Game3Neutral2
## 86 1 1 ok 5 1
## 87 1 1 ok 4 6
## 88 5 6 ok 4 1
## 89 1 1 ok 4 4
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game3Neutral3 Game4Angry1 Game4Angry2 Game4Angry3 Game4AngryFriends
## 86 2 3 1 4 1
## 87 2 2 1 7 3
## 88 6 1 1 1 1
## 89 7 1 3 1 3
## 90 NA NA NA NA NA
## 91 NA NA NA NA NA
## Game4AngryStrangers Game4CalmFriends Game4CalmStrangers Game4ExcitedFriends
## 86 1 7 7 7
## 87 4 2 6 7
## 88 1 7 5 7
## 89 3 5 4 7
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game4ExcitedStrangers Game4Exciting1 Game4Exciting2 Game4Exciting3
## 86 7 2 5 5
## 87 7 4 1 2
## 88 5 5 4 7
## 89 7 2 4 5
## 90 NA NA NA NA
## 91 NA NA NA NA
## Game4Intro Game4Neutral1 Game4Neutral2 Game4Neutral3 MusicSelectionEnd
## 86 ok 5 5 4 ok
## 87 ok 5 3 1 ok
## 88 ok 5 5 3 ok
## 89 ok 1 2 5 ok
## 90 NA NA NA
## 91 NA NA NA
## MusicSelectionInstrx RecallSelectionEnd RecallSelectionInstrx Subject2 Cond2
## 86 ok ok ok 87 1
## 87 ok ok ok 88 6
## 88 ok ok ok 89 2
## 89 ok ok ok 90 3
## 90 23 1
## 91 23 1
## Exper_A Inifile_A
## 86 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 87 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 88 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 89 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 90 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 91 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## Date_A Time_A DescribeMusic HowActiveAngry1 HowActiveAngry2
## 86 13644633600 42314 2 5 5
## 87 13644633600 53402 2 5 5
## 88 13644633600 56552 2 5 3
## 89 13644633600 60558 2 5 5
## 90 13643078400 61329 2 4 5
## 91 13643078400 63502 2 4 3
## HowActiveAngry3 HowActiveExciting1 HowActiveExciting2 HowActiveExciting3
## 86 4 5 5 5
## 87 5 5 5 5
## 88 4 4 5 5
## 89 3 5 5 5
## 90 5 3 3 3
## 91 5 4 3 5
## HowActiveNeutral1 HowActiveNeutral2 HowActiveNeutral3 HowAngryAngry1
## 86 1 1 1 3
## 87 2 2 1 5
## 88 1 2 1 5
## 89 1 1 1 5
## 90 3 4 3 3
## 91 4 4 2 2
## HowAngryAngry2 HowAngryAngry3 HowAngryExciting1 HowAngryExciting2
## 86 5 1 1 1
## 87 5 1 3 1
## 88 5 4 2 3
## 89 5 3 3 1
## 90 3 2 3 2
## 91 3 2 3 3
## HowAngryExciting3 HowAngryNeutral1 HowAngryNeutral2 HowAngryNeutral3
## 86 1 1 5 1
## 87 2 1 1 1
## 88 1 1 1 1
## 89 1 1 1 1
## 90 2 2 2 2
## 91 1 2 2 1
## HowExcitedAngry1 HowExcitedAngry2 HowExcitedAngry3 HowExcitedExciting1
## 86 4 4 4 3
## 87 5 5 5 5
## 88 5 5 4 3
## 89 5 5 5 4
## 90 4 4 5 5
## 91 3 3 3 3
## HowExcitedExciting2 HowExcitedExciting3 HowExcitedNeutral1
## 86 4 4 1
## 87 5 5 1
## 88 4 5 2
## 89 5 4 1
## 90 5 3 3
## 91 5 4 3
## HowExcitedNeutral2 HowExcitedNeutral3 HowPleasantAngry1 HowPleasantAngry2
## 86 2 1 3 3
## 87 5 5 1 1
## 88 2 1 3 3
## 89 1 2 2 1
## 90 4 4 1 1
## 91 4 3 2 2
## HowPleasantAngry3 HowPleasantExciting1 HowPleasantExciting2
## 86 4 2 4
## 87 5 5 5
## 88 2 3 3
## 89 3 1 5
## 90 1 1 2
## 91 1 2 5
## HowPleasantExciting3 HowPleasantNeutral1 HowPleasantNeutral2
## 86 3 3 3
## 87 2 5 5
## 88 5 4 4
## 89 2 4 4
## 90 1 3 3
## 91 3 5 5
## HowPleasantNeutral3 MusicRatingEnd MusicRatingInstrx WhichGames aboutyou age
## 86 2 ok ok ok ok 20
## 87 5 ok ok ok ok 18
## 88 5 ok ok ok ok 18
## 89 5 ok ok ok ok 18
## 90 3 ok ok ok ok 20
## 91 1 ok ok ok ok 20
## distractions endinstructions ethnicity overlooking race sex whatabout year
## 86 ok ok 2 ok 2 1 ok 2
## 87 ok ok 2 ok 1 1 ok 1
## 88 ok ok 2 ok 2 1 ok 1
## 89 ok ok 2 ok 2 1 ok 1
## 90 ok ok 2 ok 1 1 ok 2
## 91 ok ok 2 ok 1 1 ok 2
## Subject3 DDNoMusicLevel DDNoMusicScore DDMusicLevel DDMusicScore
## 86 87 3 0 3 170
## 87 88 3 0 3 866
## 88 89 2 3280 3 820
## 89 90 2 3040 3 0
## 90 23 2 3990 3 750
## 91 23 NA NA NA NA
## SOFNoMusicEnemies SOFNoMusicFriendlies SOFNoMusicTime SOFMusicEnemies
## 86 15 0 13140 25
## 87 24 0 23460 27
## 88 7 0 8880 31
## 89 22 2 28440 26
## 90 9 2 19260 18
## 91 NA NA NA NA
## SOFMusicFriendlies SOFMusicTime GameComments
## 86 1 23160 Participant died, restart
## 87 0 22380
## 88 0 23100
## 89 0 25500
## 90 2 24120
## 91 NA NA
## DoNotUseVideoGamePerformanceData ConfrontationalAngryMusicScore
## 86 1 4.166667
## 87 NA 6.166667
## 88 1 5.833333
## 89 NA 4.666667
## 90 NA NA
## 91 NA NA
## ConfrontationalExcitingMusicScore ConfrontationalNeutralMusicScore
## 86 1.666667 1.666667
## 87 4.833333 1.166667
## 88 2.500000 1.500000
## 89 1.666667 2.166667
## 90 NA NA
## 91 NA NA
## ConfrontationalAngryRecallScore ConfrontationalExcitingRecallScore
## 86 6.50 1.25
## 87 2.50 5.50
## 88 5.25 6.25
## 89 7.00 3.25
## 90 NA NA
## 91 NA NA
## ConfrontationalNeutralRecallScore NonconfrontationalAngryMusicScore
## 86 1.75 3.666667
## 87 4.50 3.333333
## 88 2.25 2.166667
## 89 1.00 2.000000
## 90 NA NA
## 91 NA NA
## NonconfrontationalExcitingMusicScore NonconfrontationalNeutralMusicScore
## 86 2.500000 3.666667
## 87 1.833333 3.500000
## 88 5.333333 4.000000
## 89 2.500000 3.833333
## 90 NA NA
## 91 NA NA
## NonconfrontationalAngryRecallScore NonconfrontationalExcitingRecallScore
## 86 1.25 4.25
## 87 1.75 6.00
## 88 1.00 4.25
## 89 2.25 7.00
## 90 NA NA
## 91 NA NA
## NonconfrontationalNeutralRecallScore ConfrontationalAngerScore
## 86 5.75 5.1
## 87 5.50 4.7
## 88 5.25 5.6
## 89 6.00 5.6
## 90 NA NA
## 91 NA NA
## ConfrontationalExcitingScore ConfrontationalNeutralScore
## 86 1.5 1.7
## 87 5.1 2.5
## 88 4.0 1.8
## 89 2.3 1.7
## 90 NA NA
## 91 NA NA
## NonconfrontationalAngerScore NonconfrontationalExcitingScore
## 86 2.7 3.2
## 87 2.7 3.5
## 88 1.7 4.9
## 89 2.1 4.3
## 90 NA NA
## 91 NA NA
## NonconfrontationalNeutralScore Usable DoNotUse
## 86 4.5 1 NA
## 87 4.3 1 NA
## 88 4.5 1 NA
## 89 4.7 1 NA
## 90 NA 0 1
## 91 NA 0 1
## ProblemDetails
## 86
## 87
## 88
## 89
## 90 Participant 23 was set up on part 2 of the survey when he was supposed to be set up on part 1; he did part 2 twice; data should be excluded entirely
## 91 Participant 23 was set up on part 2 of the survey when he was supposed to be set up on part 1; he did part 2 twice; data should be excluded entirely
## DinerDashWithMusicScore DinerDashWithoutMusicScore MusicCondition
## 86 5170 5000 Anger
## 87 5866 5000 Neutral
## 88 5820 3280 Exciting
## 89 5000 3040 Neutral
## 90 5750 3990 <NA>
## 91 NA NA <NA>
## ZDinerDashWithMusicScore ZDinerDashWithoutMusicScore ZSOFNoMusicEnemies
## 86 -1.02044667 0.2692740 -0.1401958
## 87 -0.02167208 0.2692740 1.0044959
## 88 -0.08768304 -1.1667773 -1.1576995
## 89 -1.26440023 -1.3671565 0.7501199
## 90 -0.18813451 -0.5739887 -0.9033236
## 91 NA NA NA
## ZSOFMusicEnemies DinerDashDifferenceScore SOFDifferenceScore
## 86 0.5785486 -1.2897207 0.71874445
## 87 0.8387424 -0.2909461 -0.16575340
## 88 1.3591301 1.0790942 2.51682964
## 89 0.7086455 0.1027563 -0.04147439
## 90 -0.3321298 0.3858541 0.57119384
## 91 NA NA NA
## PleasantScoreForAngryMusic PleasantScoreForExcitingMusic
## 86 3.333333 3.000000
## 87 2.333333 4.000000
## 88 2.666667 3.666667
## 89 2.000000 2.666667
## 90 1.000000 1.333333
## 91 1.666667 3.333333
## PleasantScoreForNeutralMusic AngryScoreForAngryMusic
## 86 2.666667 3.000000
## 87 5.000000 3.666667
## 88 4.333333 4.666667
## 89 4.333333 4.333333
## 90 3.000000 2.666667
## 91 3.666667 2.333333
## AngryScoreForExcitingMusic AngryScoreForNeutralMusic
## 86 1.000000 2.333333
## 87 2.000000 1.000000
## 88 2.000000 1.000000
## 89 1.666667 1.000000
## 90 2.333333 2.000000
## 91 2.333333 1.666667
## ExcitedScoreForExcitingMusic ExcitedScoreForNeutralMusic
## 86 3.666667 1.333333
## 87 5.000000 3.666667
## 88 4.000000 1.666667
## 89 4.333333 1.333333
## 90 4.333333 3.666667
## 91 4.000000 3.333333
## ActiveScoreForExcitingMusic ActiveScoreForNeutralMusic
## 86 5.000000 1.000000
## 87 5.000000 1.666667
## 88 4.666667 1.333333
## 89 5.000000 1.000000
## 90 3.000000 3.333333
## 91 4.000000 3.333333
## ExcitedScoreForAngryMusic ActiveScoreForAngryMusic
## 86 4.000000 4.666667
## 87 5.000000 5.000000
## 88 4.666667 4.000000
## 89 5.000000 4.333333
## 90 4.333333 4.666667
## 91 3.000000 4.000000Notice that participant 23 has missing values for part 1.
The researchers have made a column called DoNotUse based
on their exclusion criteria. Use this column to filter the dataframe!
(hint: this is a little trickier than it might be because of how R
treats NA values. You may want to use ?unique to check
values in the column and check out ?is.na.)
show(d$DoNotUse)## [1] NA 1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA 1 1filtered_d = d %>%
filter(is.na(d$DoNotUse)) # your code here: exclude subjects that are marked as "DoNotUse"
show(filtered_d)## Subject Cond Exper
## 1 1 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 2 3 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 3 4 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 4 5 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 5 6 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 6 7 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 7 8 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 8 9 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 9 10 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 10 11 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 11 12 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 12 13 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 13 14 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 14 15 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 15 16 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 16 17 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 17 18 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 18 19 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 19 20 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 20 21 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 21 22 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 22 24 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 23 25 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 24 26 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 25 27 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 26 28 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 27 29 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 28 30 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 29 31 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 30 32 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 31 33 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 32 34 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 33 35 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 34 36 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 35 37 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 36 38 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 37 39 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 38 40 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 39 41 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 40 42 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 41 43 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 42 44 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 43 45 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 44 46 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 45 47 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 46 48 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 47 49 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 48 50 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 49 51 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 50 52 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 51 53 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 52 54 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 53 55 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 54 56 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 55 57 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 56 58 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 57 59 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 58 60 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 59 61 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 60 62 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 61 63 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 62 64 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 63 65 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 64 66 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 65 67 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 66 68 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 67 69 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 68 70 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 69 71 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 70 72 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 71 73 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 72 74 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 73 75 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 74 76 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 75 77 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 76 78 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 77 79 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 78 80 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 79 81 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 80 82 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 81 83 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 82 84 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 83 85 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 84 86 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 85 87 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 86 88 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 87 89 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## 88 90 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part1.exp
## Inifile Date Time Game1Angry1 Game1Angry2 Game1Angry3
## 1 default.mlp 13642819200 40781 6 6 5
## 2 default.mlp 13642819200 54540 6 5 7
## 3 default.mlp 13642905600 34952 4 1 1
## 4 default.mlp 13642905600 49095 6 6 7
## 5 default.mlp 13642905600 59714 5 5 6
## 6 default.mlp 13642905600 59717 6 6 6
## 7 default.mlp 13642992000 33185 5 4 5
## 8 default.mlp 13642992000 36299 4 1 4
## 9 default.mlp 13642992000 47504 7 5 7
## 10 default.mlp 13642992000 50951 3 4 3
## 11 default.mlp 13642992000 50998 5 6 1
## 12 default.mlp 13642992000 58250 4 6 5
## 13 default.mlp 13642992000 57818 2 5 4
## 14 default.mlp 13642992000 61779 6 1 6
## 15 default.mlp 13642992000 62005 4 5 5
## 16 default.mlp 13643078400 47098 3 5 7
## 17 default.mlp 13643078400 47311 7 7 5
## 18 default.mlp 13643078400 50697 7 4 5
## 19 default.mlp 13643078400 50811 5 3 7
## 20 default.mlp 13643078400 53975 4 1 4
## 21 default.mlp 13643078400 54359 4 2 2
## 22 default.mlp 13643164800 33135 5 5 4
## 23 default.mlp 13643164800 37160 4 7 6
## 24 default.mlp 13643164800 36800 6 2 6
## 25 default.mlp 13643164800 40179 4 4 7
## 26 default.mlp 13643164800 40305 7 6 6
## 27 default.mlp 13643164800 47391 6 6 7
## 28 default.mlp 13643164800 51178 1 3 6
## 29 default.mlp 13643164800 55067 3 6 1
## 30 default.mlp 13643424000 33285 5 3 6
## 31 default.mlp 13643424000 33384 7 7 4
## 32 default.mlp 13643424000 36514 4 5 5
## 33 default.mlp 13643424000 40163 2 2 3
## 34 default.mlp 13643424000 50744 6 5 5
## 35 default.mlp 13643424000 51158 4 4 7
## 36 default.mlp 13643596800 32883 1 5 4
## 37 default.mlp 13643596800 36678 3 5 6
## 38 default.mlp 13643596800 47309 5 5 5
## 39 default.mlp 13643596800 54412 6 4 6
## 40 default.mlp 13643596800 50805 6 6 7
## 41 default.mlp 13643596800 54392 5 6 7
## 42 default.mlp 13643596800 57907 5 6 5
## 43 default.mlp 13643596800 58055 5 5 6
## 44 default.mlp 13643596800 61559 1 1 6
## 45 default.mlp 13643596800 61653 4 2 5
## 46 default.mlp 13643683200 47348 3 3 6
## 47 default.mlp 13643683200 51896 5 6 5
## 48 default.mlp 13643683200 58399 6 6 7
## 49 default.mlp 13643683200 58093 7 4 7
## 50 default.mlp 13643683200 61688 5 3 4
## 51 default.mlp 13643683200 61526 7 6 6
## 52 default.mlp 13643769600 33015 3 6 7
## 53 default.mlp 13643769600 36550 7 6 6
## 54 default.mlp 13643769600 40071 3 1 5
## 55 default.mlp 13643769600 51257 3 3 4
## 56 default.mlp 13643769600 54100 5 1 7
## 57 default.mlp 13644028800 39776 7 7 7
## 58 default.mlp 13644028800 50941 6 7 5
## 59 default.mlp 13644028800 50893 7 7 7
## 60 default.mlp 13644115200 46389 6 2 6
## 61 default.mlp 13644115200 49305 6 7 5
## 62 default.mlp 13644115200 52597 6 6 7
## 63 default.mlp 13644115200 57016 7 3 5
## 64 default.mlp 13644115200 57017 7 4 7
## 65 default.mlp 13644115200 60094 1 1 1
## 66 default.mlp 13644115200 60278 6 7 6
## 67 default.mlp 13644201600 36667 7 7 7
## 68 default.mlp 13644201600 47428 5 5 7
## 69 default.mlp 13644201600 54401 6 6 1
## 70 default.mlp 13644201600 54841 1 7 5
## 71 default.mlp 13644201600 58109 3 1 4
## 72 default.mlp 13644201600 58319 4 5 7
## 73 default.mlp 13644201600 61650 6 5 2
## 74 default.mlp 13644374400 32809 6 5 5
## 75 default.mlp 13644374400 36986 6 5 5
## 76 default.mlp 13644374400 39875 7 7 7
## 77 default.mlp 13644374400 47139 3 4 6
## 78 default.mlp 13644374400 50863 5 1 3
## 79 default.mlp 13644374400 50929 5 5 7
## 80 default.mlp 13644374400 58020 6 6 5
## 81 default.mlp 13644374400 54775 7 6 4
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## 87 default.mlp 13644633600 54293 7 6 6
## 88 default.mlp 13644633600 58190 5 5 5
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## Game2Angry1 Game2Angry2 Game2Angry3 Game2AngryFriends Game2AngryStrangers
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## Game2CalmFriends Game2CalmStrangers Game2ExcitedFriends
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## Game2ExcitedStrangers Game2Exciting1 Game2Exciting2 Game2Exciting3
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## Game2Intro Game2Neutral1 Game2Neutral2 Game2Neutral3 Game3Angry1 Game3Angry2
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## Game3Angry3 Game3AngryFriends Game3AngryStrangers Game3CalmFriends
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## Game3CalmStrangers Game3ExcitedFriends Game3ExcitedStrangers Game3Exciting1
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## Game3Neutral3 Game4Angry1 Game4Angry2 Game4Angry3 Game4AngryFriends
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## 34 5 4 4 2 2
## 35 2 7 6 1 2
## 36 6 1 1 2 1
## 37 4 1 1 3 2
## 38 3 4 5 5 4
## 39 6 5 4 4 4
## 40 5 3 2 2 2
## 41 1 1 1 4 1
## 42 3 4 5 6 3
## 43 6 4 4 3 5
## 44 6 2 2 4 3
## 45 6 6 2 3 4
## 46 5 5 2 6 3
## 47 5 2 3 3 3
## 48 7 1 1 4 1
## 49 4 1 5 6 3
## 50 5 2 1 2 2
## 51 3 3 1 2 2
## 52 5 2 1 3 1
## 53 3 3 4 5 1
## 54 2 1 1 1 1
## 55 5 2 2 5 1
## 56 2 4 2 6 1
## 57 5 3 3 3 1
## 58 4 2 5 2 1
## 59 6 1 2 5 1
## 60 2 4 2 5 1
## 61 1 2 3 2 1
## 62 4 4 3 3 2
## 63 5 1 1 1 5
## 64 5 1 7 4 1
## 65 4 1 1 5 1
## 66 4 4 5 4 4
## 67 4 3 3 5 3
## 68 3 1 1 1 1
## 69 3 1 1 1 3
## 70 5 5 3 4 2
## 71 2 5 5 6 1
## 72 3 3 2 5 1
## 73 2 1 2 1 2
## 74 3 3 2 2 2
## 75 2 1 1 2 1
## 76 3 7 1 5 4
## 77 7 3 3 2 3
## 78 7 1 1 1 1
## 79 5 2 1 5 4
## 80 1 2 2 1 2
## 81 1 4 1 3 1
## 82 7 2 1 1 1
## 83 2 1 3 3 2
## 84 1 3 3 2 2
## 85 2 3 1 4 1
## 86 2 2 1 7 3
## 87 6 1 1 1 1
## 88 7 1 3 1 3
## Game4AngryStrangers Game4CalmFriends Game4CalmStrangers Game4ExcitedFriends
## 1 2 5 5 7
## 2 5 2 4 4
## 3 1 2 2 4
## 4 3 5 5 5
## 5 2 4 4 5
## 6 1 4 3 5
## 7 2 4 2 7
## 8 1 1 1 4
## 9 2 1 1 6
## 10 4 3 4 3
## 11 2 4 6 7
## 12 2 3 5 7
## 13 1 3 2 6
## 14 1 7 7 7
## 15 5 5 4 7
## 16 1 3 2 7
## 17 3 4 3 7
## 18 1 7 6 3
## 19 1 5 4 3
## 20 1 4 5 5
## 21 1 7 4 7
## 22 1 3 4 5
## 23 5 3 2 5
## 24 1 7 6 3
## 25 2 4 6 4
## 26 1 3 4 7
## 27 1 2 4 7
## 28 1 4 4 7
## 29 5 3 4 3
## 30 3 2 2 2
## 31 2 5 4 4
## 32 4 6 6 5
## 33 1 2 2 7
## 34 2 5 5 6
## 35 2 4 3 5
## 36 1 4 5 3
## 37 6 3 2 7
## 38 3 3 3 5
## 39 2 6 5 7
## 40 1 3 5 7
## 41 1 5 4 7
## 42 4 4 5 4
## 43 5 4 4 4
## 44 4 6 4 6
## 45 4 4 4 4
## 46 2 5 4 7
## 47 2 4 4 5
## 48 1 7 3 7
## 49 2 4 5 6
## 50 2 5 4 5
## 51 2 5 4 7
## 52 1 3 2 6
## 53 1 6 6 4
## 54 5 4 4 4
## 55 2 4 3 6
## 56 1 1 1 7
## 57 2 3 1 7
## 58 1 5 4 6
## 59 1 4 2 7
## 60 3 2 1 7
## 61 1 5 2 7
## 62 3 4 3 7
## 63 4 3 3 4
## 64 1 4 4 5
## 65 1 6 3 6
## 66 4 4 4 7
## 67 1 6 2 6
## 68 1 1 1 7
## 69 1 6 5 3
## 70 2 5 1 7
## 71 1 1 1 7
## 72 1 4 4 7
## 73 2 3 4 7
## 74 2 2 5 4
## 75 1 2 2 6
## 76 2 5 2 7
## 77 2 7 5 6
## 78 1 1 1 5
## 79 4 6 5 7
## 80 1 4 3 5
## 81 1 6 5 7
## 82 1 1 1 7
## 83 2 3 2 4
## 84 3 5 3 5
## 85 1 7 7 7
## 86 4 2 6 7
## 87 1 7 5 7
## 88 3 5 4 7
## Game4ExcitedStrangers Game4Exciting1 Game4Exciting2 Game4Exciting3
## 1 4 5 5 2
## 2 5 7 4 5
## 3 4 6 6 6
## 4 6 1 5 5
## 5 4 2 4 3
## 6 5 6 5 6
## 7 6 4 5 6
## 8 1 4 7 3
## 9 3 5 6 4
## 10 6 1 4 5
## 11 7 3 4 6
## 12 4 4 6 2
## 13 4 3 5 3
## 14 7 3 6 5
## 15 4 2 2 4
## 16 5 4 6 5
## 17 5 2 2 2
## 18 2 4 5 4
## 19 6 2 4 5
## 20 4 4 3 2
## 21 7 6 3 1
## 22 4 1 3 2
## 23 2 1 5 4
## 24 2 3 5 5
## 25 4 4 3 4
## 26 6 4 5 6
## 27 6 3 1 4
## 28 4 1 4 4
## 29 4 4 7 5
## 30 6 2 4 5
## 31 4 6 5 5
## 32 6 3 5 5
## 33 2 3 7 6
## 34 5 4 5 5
## 35 3 5 7 6
## 36 5 1 2 1
## 37 4 1 5 1
## 38 5 2 6 5
## 39 5 2 2 5
## 40 6 4 6 6
## 41 5 6 3 3
## 42 5 1 4 2
## 43 3 6 5 6
## 44 3 2 2 2
## 45 4 3 1 3
## 46 7 2 3 5
## 47 5 4 4 6
## 48 5 1 7 2
## 49 6 3 4 7
## 50 5 5 6 5
## 51 7 4 7 5
## 52 7 3 6 7
## 53 4 3 6 5
## 54 4 1 1 2
## 55 3 3 6 3
## 56 6 3 3 3
## 57 6 5 5 5
## 58 5 3 7 5
## 59 6 3 7 5
## 60 6 3 3 6
## 61 6 5 6 7
## 62 5 3 5 6
## 63 3 2 3 3
## 64 5 7 3 4
## 65 3 1 2 1
## 66 5 4 4 5
## 67 6 4 2 4
## 68 7 7 7 6
## 69 4 1 1 1
## 70 6 5 6 6
## 71 7 6 7 5
## 72 7 5 2 4
## 73 6 1 5 5
## 74 6 2 5 1
## 75 5 2 4 1
## 76 3 7 7 7
## 77 6 1 6 1
## 78 5 1 5 4
## 79 7 1 4 6
## 80 4 5 7 5
## 81 7 3 6 7
## 82 7 7 7 7
## 83 4 1 4 1
## 84 4 3 5 5
## 85 7 2 5 5
## 86 7 4 1 2
## 87 5 5 4 7
## 88 7 2 4 5
## Game4Intro Game4Neutral1 Game4Neutral2 Game4Neutral3 MusicSelectionEnd
## 1 ok 1 5 2 ok
## 2 ok 3 2 4 ok
## 3 ok 4 5 2 ok
## 4 ok 4 2 5 ok
## 5 ok 3 5 5 ok
## 6 ok 1 1 1 ok
## 7 ok 3 2 2 ok
## 8 ok 6 2 2 ok
## 9 ok 2 4 2 ok
## 10 ok 1 5 2 ok
## 11 ok 4 5 1 ok
## 12 ok 3 3 3 ok
## 13 ok 5 5 2 ok
## 14 ok 7 7 7 ok
## 15 ok 2 3 4 ok
## 16 ok 7 3 3 ok
## 17 ok 1 2 1 ok
## 18 ok 6 7 6 ok
## 19 ok 4 5 3 ok
## 20 ok 2 1 2 ok
## 21 ok 5 1 2 ok
## 22 ok 5 3 5 ok
## 23 ok 7 7 5 ok
## 24 ok 6 6 7 ok
## 25 ok 3 3 1 ok
## 26 ok 1 1 1 ok
## 27 ok 6 6 1 ok
## 28 ok 7 7 5 ok
## 29 ok 6 5 2 ok
## 30 ok 4 2 3 ok
## 31 ok 4 4 2 ok
## 32 ok 7 6 4 ok
## 33 ok 4 5 3 ok
## 34 ok 4 3 3 ok
## 35 ok 3 4 7 ok
## 36 ok 6 5 4 ok
## 37 ok 4 6 4 ok
## 38 ok 3 4 3 ok
## 39 ok 3 2 6 ok
## 40 ok 4 1 1 ok
## 41 ok 5 2 2 ok
## 42 ok 2 5 4 ok
## 43 ok 5 3 2 ok
## 44 ok 4 1 2 ok
## 45 ok 1 5 4 ok
## 46 ok 6 6 4 ok
## 47 ok 5 3 3 ok
## 48 ok 5 6 6 ok
## 49 ok 3 5 4 ok
## 50 ok 4 5 4 ok
## 51 ok 6 1 1 ok
## 52 ok 6 3 2 ok
## 53 ok 6 6 2 ok
## 54 ok 3 1 2 ok
## 55 ok 5 5 4 ok
## 56 ok 5 1 1 ok
## 57 ok 4 4 4 ok
## 58 ok 6 4 1 ok
## 59 ok 7 7 3 ok
## 60 ok 1 3 3 ok
## 61 ok 5 2 1 ok
## 62 ok 6 5 3 ok
## 63 ok 3 2 4 ok
## 64 ok 6 7 1 ok
## 65 ok 2 3 4 ok
## 66 ok 3 2 2 ok
## 67 ok 6 3 1 ok
## 68 ok 4 4 4 ok
## 69 ok 5 6 5 ok
## 70 ok 1 2 4 ok
## 71 ok 2 2 2 ok
## 72 ok 4 2 1 ok
## 73 ok 5 4 1 ok
## 74 ok 2 1 1 ok
## 75 ok 7 7 1 ok
## 76 ok 4 3 2 ok
## 77 ok 6 6 6 ok
## 78 ok 7 7 1 ok
## 79 ok 7 5 3 ok
## 80 ok 6 6 4 ok
## 81 ok 1 1 1 ok
## 82 ok 3 3 2 ok
## 83 ok 1 1 4 ok
## 84 ok 3 4 1 ok
## 85 ok 5 5 4 ok
## 86 ok 5 3 1 ok
## 87 ok 5 5 3 ok
## 88 ok 1 2 5 ok
## MusicSelectionInstrx RecallSelectionEnd RecallSelectionInstrx Subject2 Cond2
## 1 ok ok ok 1 2
## 2 ok ok ok 3 1
## 3 ok ok ok 4 4
## 4 ok ok ok 5 5
## 5 ok ok ok 6 6
## 6 ok ok ok 7 3
## 7 ok ok ok 8 6
## 8 ok ok ok 9 5
## 9 ok ok ok 10 1
## 10 ok ok ok 11 2
## 11 ok ok ok 12 4
## 12 ok ok ok 13 4
## 13 ok ok ok 14 6
## 14 ok ok ok 15 2
## 15 ok ok ok 16 3
## 16 ok ok ok 17 5
## 17 ok ok ok 18 1
## 18 ok ok ok 19 4
## 19 ok ok ok 20 3
## 20 ok ok ok 21 6
## 21 ok ok ok 22 5
## 22 ok ok ok 24 2
## 23 ok ok ok 25 2
## 24 ok ok ok 26 1
## 25 ok ok ok 27 3
## 26 ok ok ok 28 4
## 27 ok ok ok 29 6
## 28 ok ok ok 30 5
## 29 ok ok ok 31 4
## 30 ok ok ok 32 5
## 31 ok ok ok 33 3
## 32 ok ok ok 34 1
## 33 ok ok ok 35 2
## 34 ok ok ok 36 6
## 35 ok ok ok 37 1
## 36 ok ok ok 38 6
## 37 ok ok ok 39 4
## 38 ok ok ok 40 3
## 39 ok ok ok 41 5
## 40 ok ok ok 42 2
## 41 ok ok ok 43 6
## 42 ok ok ok 44 2
## 43 ok ok ok 45 3
## 44 ok ok ok 46 1
## 45 ok ok ok 47 4
## 46 ok ok ok 48 5
## 47 ok ok ok 49 5
## 48 ok ok ok 50 3
## 49 ok ok ok 51 4
## 50 ok ok ok 52 1
## 51 ok ok ok 53 6
## 52 ok ok ok 54 2
## 53 ok ok ok 55 4
## 54 ok ok ok 56 3
## 55 ok ok ok 57 2
## 56 ok ok ok 58 5
## 57 ok ok ok 59 1
## 58 ok ok ok 60 6
## 59 ok ok ok 61 3
## 60 ok ok ok 62 6
## 61 ok ok ok 63 1
## 62 ok ok ok 64 2
## 63 ok ok ok 65 4
## 64 ok ok ok 66 5
## 65 ok ok ok 67 4
## 66 ok ok ok 68 3
## 67 ok ok ok 69 6
## 68 ok ok ok 70 2
## 69 ok ok ok 71 5
## 70 ok ok ok 72 1
## 71 ok ok ok 73 1
## 72 ok ok ok 74 2
## 73 ok ok ok 75 6
## 74 ok ok ok 76 5
## 75 ok ok ok 77 4
## 76 ok ok ok 78 3
## 77 ok ok ok 79 6
## 78 ok ok ok NA NA
## 79 ok ok ok 81 5
## 80 ok ok ok 82 3
## 81 ok ok ok 83 4
## 82 ok ok ok 84 4
## 83 ok ok ok 85 5
## 84 ok ok ok 86 3
## 85 ok ok ok 87 1
## 86 ok ok ok 88 6
## 87 ok ok ok 89 2
## 88 ok ok ok 90 3
## Exper_A Inifile_A
## 1 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 2 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 3 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 4 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 5 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 6 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 7 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 8 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 9 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 10 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 11 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 12 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 13 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 14 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 15 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 16 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 17 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 18 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 19 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 20 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 21 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 22 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 23 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 24 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 25 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 26 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 27 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 28 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 29 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 30 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 31 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 32 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 33 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 34 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 35 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 36 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 37 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 38 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 39 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 40 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 41 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 42 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 43 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 44 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 45 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 46 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 47 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 48 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 49 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 50 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 51 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 52 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 53 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 54 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 55 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 56 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 57 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 58 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 59 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 60 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 61 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 62 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 63 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 64 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 65 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 66 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 67 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 68 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 69 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 70 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 71 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 72 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 73 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 74 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 75 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 76 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 77 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 78
## 79 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 80 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 81 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 82 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 83 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 84 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 85 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 86 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 87 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## 88 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
## Date_A Time_A DescribeMusic HowActiveAngry1 HowActiveAngry2
## 1 13642819200 43151 2 4 4
## 2 13642819200 57041 2 4 4
## 3 13642905600 37630 3 5 3
## 4 13642905600 51434 2 5 4
## 5 13642905600 62320 3 3 3
## 6 13642905600 62209 3 5 5
## 7 13642992000 35643 3 4 3
## 8 13642992000 38665 2 3 3
## 9 13642992000 49847 1 5 4
## 10 13642992000 53401 2 5 4
## 11 13642992000 53299 3 5 5
## 12 13642992000 61398 1 5 5
## 13 13642992000 60211 3 3 4
## 14 13642992000 64439 2 2 4
## 15 13642992000 64661 3 2 5
## 16 13643078400 49625 2 3 4
## 17 13643078400 49818 2 5 5
## 18 13643078400 53174 2 5 4
## 19 13643078400 53056 3 4 4
## 20 13643078400 56544 3 3 3
## 21 13643078400 56687 2 4 3
## 22 13643164800 35368 2 5 4
## 23 13643164800 39515 2 3 5
## 24 13643164800 39052 3 5 4
## 25 13643164800 42366 3 5 5
## 26 13643164800 42624 2 5 5
## 27 13643164800 49685 3 5 4
## 28 13643164800 53380 2 4 3
## 29 13643164800 57341 2 5 5
## 30 13643424000 35273 3 3 3
## 31 13643424000 35561 3 5 4
## 32 13643424000 38902 2 4 4
## 33 13643424000 42463 2 4 3
## 34 13643424000 53140 3 3 3
## 35 13643424000 53486 3 4 3
## 36 13643596800 35111 3 4 4
## 37 13643596800 39014 3 1 1
## 38 13643596800 49509 3 3 3
## 39 13643596800 56639 2 5 5
## 40 13643596800 52998 2 4 4
## 41 13643596800 56744 3 5 5
## 42 13643596800 60083 2 3 4
## 43 13643596800 60410 2 5 5
## 44 13643596800 63910 1 2 3
## 45 13643596800 65196 1 3 3
## 46 13643683200 49774 2 4 4
## 47 13643683200 54140 2 5 5
## 48 13643683200 60639 3 4 4
## 49 13643683200 60261 1 5 4
## 50 13643683200 64173 2 3 2
## 51 13643683200 63747 3 4 5
## 52 13643769600 35193 2 5 4
## 53 13643769600 38792 2 5 5
## 54 13643769600 42282 3 4 4
## 55 13643769600 53640 2 2 2
## 56 13643769600 57171 2 4 4
## 57 13644028800 42012 2 4 5
## 58 13644028800 53179 2 5 5
## 59 13644028800 53228 3 5 5
## 60 13644115200 48559 3 5 3
## 61 13644115200 51680 3 5 5
## 62 13644115200 54898 2 4 4
## 63 13644115200 59667 2 5 5
## 64 13644115200 59449 2 5 5
## 65 13644115200 62294 1 1 1
## 66 13644115200 62661 3 4 3
## 67 13644201600 39038 3 4 5
## 68 13644201600 49568 2 4 5
## 69 13644201600 56662 2 5 5
## 70 13644201600 57323 2 5 5
## 71 13644201600 60432 1 4 4
## 72 13644201600 60888 2 4 2
## 73 13644201600 63978 3 3 3
## 74 13644374400 35002 2 4 1
## 75 13644374400 39167 2 4 5
## 76 13644374400 42036 3 5 4
## 77 13644374400 49570 2 4 5
## 78 NA NA NA NA NA
## 79 13644374400 53231 2 4 4
## 80 13644374400 60664 3 4 4
## 81 13644374400 57215 2 5 3
## 82 13644374400 64189 2 5 3
## 83 13644374400 63914 2 4 3
## 84 13644633600 35448 3 4 5
## 85 13644633600 42314 2 5 5
## 86 13644633600 53402 2 5 5
## 87 13644633600 56552 2 5 3
## 88 13644633600 60558 2 5 5
## HowActiveAngry3 HowActiveExciting1 HowActiveExciting2 HowActiveExciting3
## 1 4 5 4 5
## 2 4 2 1 3
## 3 3 5 5 5
## 4 5 3 3 3
## 5 2 3 3 4
## 6 3 4 4 2
## 7 3 5 4 5
## 8 5 5 4 1
## 9 3 4 3 5
## 10 2 3 3 3
## 11 4 4 3 4
## 12 3 5 5 4
## 13 3 4 3 4
## 14 3 5 5 4
## 15 5 4 4 3
## 16 5 3 1 3
## 17 4 5 5 5
## 18 5 4 3 4
## 19 5 3 3 4
## 20 3 5 5 5
## 21 2 5 3 3
## 22 2 5 4 5
## 23 4 5 5 4
## 24 2 4 5 5
## 25 4 3 4 4
## 26 4 3 4 4
## 27 3 5 4 4
## 28 3 5 4 5
## 29 2 4 5 5
## 30 3 3 4 2
## 31 3 5 5 5
## 32 5 4 5 4
## 33 2 4 5 5
## 34 4 3 4 4
## 35 3 2 5 5
## 36 4 5 5 5
## 37 1 3 5 4
## 38 3 3 2 2
## 39 5 5 5 4
## 40 2 4 5 5
## 41 4 4 4 5
## 42 4 1 3 1
## 43 4 4 4 5
## 44 3 2 3 1
## 45 4 4 4 4
## 46 4 5 5 5
## 47 4 5 5 5
## 48 3 5 4 5
## 49 5 5 4 4
## 50 4 3 4 5
## 51 4 4 4 5
## 52 4 5 5 5
## 53 5 5 5 5
## 54 4 3 3 4
## 55 1 3 4 3
## 56 5 5 4 4
## 57 4 4 4 4
## 58 3 5 3 3
## 59 5 5 5 5
## 60 4 5 3 5
## 61 5 4 4 5
## 62 3 5 5 5
## 63 4 5 4 5
## 64 5 5 3 3
## 65 2 1 3 1
## 66 4 4 4 4
## 67 4 4 4 5
## 68 3 5 5 5
## 69 2 3 5 5
## 70 3 4 5 3
## 71 4 5 5 5
## 72 4 5 5 5
## 73 4 4 5 3
## 74 5 2 3 3
## 75 5 1 3 1
## 76 5 5 5 4
## 77 3 4 4 4
## 78 NA NA NA NA
## 79 4 4 5 3
## 80 3 4 4 5
## 81 1 4 4 5
## 82 1 5 4 5
## 83 3 2 4 4
## 84 4 4 4 4
## 85 4 5 5 5
## 86 5 5 5 5
## 87 4 4 5 5
## 88 3 5 5 5
## HowActiveNeutral1 HowActiveNeutral2 HowActiveNeutral3 HowAngryAngry1
## 1 2 2 2 5
## 2 1 2 1 4
## 3 2 2 1 3
## 4 2 1 1 2
## 5 1 2 1 2
## 6 1 1 3 4
## 7 2 1 2 4
## 8 1 3 2 1
## 9 2 1 1 3
## 10 2 1 2 3
## 11 1 2 1 5
## 12 2 1 2 4
## 13 2 2 1 3
## 14 2 4 2 4
## 15 2 1 1 4
## 16 3 2 1 2
## 17 3 2 2 4
## 18 3 2 1 5
## 19 1 1 1 4
## 20 2 1 1 3
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## HowPleasantAngry3 HowPleasantExciting1 HowPleasantExciting2
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## HowPleasantExciting3 HowPleasantNeutral1 HowPleasantNeutral2
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## 88 2 4 4
## HowPleasantNeutral3 MusicRatingEnd MusicRatingInstrx WhichGames aboutyou age
## 1 5 ok ok ok ok 18
## 2 1 ok ok ok ok 18
## 3 5 ok ok ok ok 18
## 4 5 ok ok ok ok 18
## 5 4 ok ok ok ok 19
## 6 2 ok ok ok ok 18
## 7 5 ok ok ok ok 21
## 8 5 ok ok ok ok 19
## 9 4 ok ok ok ok 19
## 10 3 ok ok ok ok 19
## 11 5 ok ok ok ok 19
## 12 5 ok ok ok ok 19
## 13 4 ok ok ok ok 18
## 14 4 ok ok ok ok 18
## 15 4 ok ok ok ok 18
## 16 5 ok ok ok ok 19
## 17 4 ok ok ok ok 17
## 18 5 ok ok ok ok 18
## 19 5 ok ok ok ok 18
## 20 5 ok ok ok ok 22
## 21 3 ok ok ok ok 19
## 22 4 ok ok ok ok 18
## 23 3 ok ok ok ok 19
## 24 5 ok ok ok ok 18
## 25 4 ok ok ok ok 19
## 26 4 ok ok ok ok 18
## 27 5 ok ok ok ok 20
## 28 5 ok ok ok ok 20
## 29 4 ok ok ok ok 21
## 30 3 ok ok ok ok 18
## 31 4 ok ok ok ok 18
## 32 4 ok ok ok ok 18
## 33 5 ok ok ok ok 20
## 34 4 ok ok ok ok 20
## 35 5 ok ok ok ok 18
## 36 5 ok ok ok ok 20
## 37 5 ok ok ok ok 20
## 38 2 ok ok ok ok 19
## 39 5 ok ok ok ok 19
## 40 4 ok ok ok ok 19
## 41 4 ok ok ok ok 18
## 42 2 ok ok ok ok 19
## 43 5 ok ok ok ok 19
## 44 5 ok ok ok ok 19
## 45 5 ok ok ok ok 20
## 46 1 ok ok ok ok 19
## 47 4 ok ok ok ok 21
## 48 5 ok ok ok ok 19
## 49 4 ok ok ok ok 19
## 50 4 ok ok ok ok 19
## 51 4 ok ok ok ok 19
## 52 5 ok ok ok ok 19
## 53 5 ok ok ok ok 19
## 54 4 ok ok ok ok 20
## 55 3 ok ok ok ok 19
## 56 4 ok ok ok ok 21
## 57 4 ok ok ok ok 19
## 58 5 ok ok ok ok 18
## 59 5 ok ok ok ok 19
## 60 4 ok ok ok ok 18
## 61 4 ok ok ok ok 18
## 62 5 ok ok ok ok 20
## 63 5 ok ok ok ok 19
## 64 4 ok ok ok ok 19
## 65 4 ok ok ok ok 18
## 66 5 ok ok ok ok 19
## 67 5 ok ok ok ok 22
## 68 5 ok ok ok ok 22
## 69 5 ok ok ok ok 21
## 70 4 ok ok ok ok 22
## 71 2 ok ok ok ok 19
## 72 3 ok ok ok ok 19
## 73 4 ok ok ok ok 19
## 74 5 ok ok ok ok 19
## 75 5 ok ok ok ok 20
## 76 4 ok ok ok ok 22
## 77 1 ok ok ok ok 19
## 78 NA NA
## 79 5 ok ok ok ok 20
## 80 5 ok ok ok ok 19
## 81 1 ok ok ok ok 19
## 82 4 ok ok ok ok 18
## 83 4 ok ok ok ok 19
## 84 4 ok ok ok ok 19
## 85 2 ok ok ok ok 20
## 86 5 ok ok ok ok 18
## 87 5 ok ok ok ok 18
## 88 5 ok ok ok ok 18
## distractions endinstructions ethnicity overlooking race sex whatabout year
## 1 ok ok 2 ok 2 1 ok 1
## 2 ok ok 2 ok 2 1 ok 1
## 3 ok ok 2 ok 2 1 ok 1
## 4 ok ok 2 ok 2 1 ok 1
## 5 ok ok 2 ok 2 1 ok 1
## 6 ok ok 2 ok 1 1 ok 1
## 7 ok ok 2 ok 2 1 ok 3
## 8 ok ok 2 ok 3 1 ok 2
## 9 ok ok 2 ok 2 1 ok 1
## 10 ok ok 2 ok 2 1 ok 1
## 11 ok ok 2 ok 2 1 ok 2
## 12 ok ok 2 ok 2 1 ok 2
## 13 ok ok 2 ok 2 1 ok 1
## 14 ok ok 2 ok 2 1 ok 1
## 15 ok ok 2 ok 2 1 ok 1
## 16 ok ok 2 ok 3 1 ok 1
## 17 ok ok 1 ok 5 1 ok 1
## 18 ok ok 2 ok 2 1 ok 1
## 19 ok ok 2 ok 2 1 ok 1
## 20 ok ok 2 ok 2 1 ok 4
## 21 ok ok 2 ok 2 1 ok 1
## 22 ok ok 2 ok 2 1 ok 1
## 23 ok ok 2 ok 2 1 ok 2
## 24 ok ok 2 ok 2 1 ok 1
## 25 ok ok 2 ok 2 1 ok 1
## 26 ok ok 2 ok 2 1 ok 1
## 27 ok ok 2 ok 2 1 ok 2
## 28 ok ok 2 ok 2 1 ok 3
## 29 ok ok 2 ok 1 1 ok 4
## 30 ok ok 2 ok 3 1 ok 1
## 31 ok ok 2 ok 6 1 ok 1
## 32 ok ok 2 ok 3 1 ok 1
## 33 ok ok 2 ok 3 1 ok 2
## 34 ok ok 2 ok 3 1 ok 1
## 35 ok ok 2 ok 3 1 ok 1
## 36 ok ok 2 ok 2 1 ok 1
## 37 ok ok 1 ok 1 1 ok 2
## 38 ok ok 2 ok 6 1 ok 1
## 39 ok ok 2 ok 2 1 ok 1
## 40 ok ok 2 ok 2 1 ok 1
## 41 ok ok 2 ok 2 1 ok 1
## 42 ok ok 2 ok 3 1 ok 2
## 43 ok ok 2 ok 2 1 ok 2
## 44 ok ok 2 ok 2 1 ok 1
## 45 ok ok 2 ok 3 1 ok 2
## 46 ok ok 1 ok 6 1 ok 2
## 47 ok ok 1 ok 6 1 ok 4
## 48 ok ok 2 ok 2 1 ok 1
## 49 ok ok 2 ok 2 1 ok 1
## 50 ok ok 2 ok 2 1 ok 1
## 51 ok ok 2 ok 3 1 ok 2
## 52 ok ok 2 ok 2 1 ok 1
## 53 ok ok 2 ok 2 1 ok 1
## 54 ok ok 2 ok 2 1 ok 2
## 55 ok ok 2 ok 2 1 ok 2
## 56 ok ok 2 ok 3 1 ok 3
## 57 ok ok 2 ok 2 1 ok 1
## 58 ok ok 1 ok 5 1 ok 1
## 59 ok ok 1 ok 2 1 ok 1
## 60 ok ok 2 ok 2 1 ok 1
## 61 ok ok 2 ok 1 1 ok 1
## 62 ok ok 2 ok 2 1 ok 2
## 63 ok ok 2 ok 3 1 ok 2
## 64 ok ok 2 ok 2 1 ok 2
## 65 ok ok 2 ok 2 1 ok 1
## 66 ok ok 2 ok 2 1 ok 1
## 67 ok ok 2 ok 2 1 ok 4
## 68 ok ok 2 ok 2 1 ok 4
## 69 ok ok 2 ok 2 1 ok 4
## 70 ok ok 2 ok 2 1 ok 4
## 71 ok ok 2 ok 6 1 ok 2
## 72 ok ok 2 ok 2 1 ok 1
## 73 ok ok 2 ok 2 1 ok 1
## 74 ok ok 2 ok 2 1 ok 1
## 75 ok ok 2 ok 2 1 ok 2
## 76 ok ok 2 ok 2 1 ok 4
## 77 ok ok 2 ok 3 1 ok 1
## 78 NA NA NA NA
## 79 ok ok 2 ok 2 1 ok 2
## 80 ok ok 2 ok 2 1 ok 1
## 81 ok ok 2 ok 2 1 ok 1
## 82 ok ok 2 ok 2 1 ok 1
## 83 ok ok 2 ok 2 1 ok 1
## 84 ok ok 2 ok 2 1 ok 1
## 85 ok ok 2 ok 2 1 ok 2
## 86 ok ok 2 ok 1 1 ok 1
## 87 ok ok 2 ok 2 1 ok 1
## 88 ok ok 2 ok 2 1 ok 1
## Subject3 DDNoMusicLevel DDNoMusicScore DDMusicLevel DDMusicScore
## 1 1 3 0 3 830
## 2 3 2 1250 3 370
## 3 4 3 1742 3 1921
## 4 5 3 60 3 1750
## 5 6 3 840 3 1380
## 6 7 3 20 3 170
## 7 8 3 0 3 690
## 8 9 3 1460 3 1440
## 9 10 2 2990 3 480
## 10 11 3 90 3 1210
## 11 12 3 490 3 1270
## 12 13 3 140 3 1150
## 13 14 3 NA 3 2440
## 14 15 3 0 3 660
## 15 16 3 200 3 1810
## 16 17 2 3040 3 950
## 17 18 3 140 3 1160
## 18 19 3 370 3 1240
## 19 20 3 170 3 1650
## 20 21 2 3000 3 1500
## 21 22 3 0 3 770
## 22 24 3 60 3 950
## 23 25 3 0 3 550
## 24 26 3 20 3 1560
## 25 27 3 370 3 1190
## 26 28 3 0 3 930
## 27 29 3 0 3 990
## 28 30 3 960 3 1160
## 29 31 2 970 3 20
## 30 32 2 1090 3 0
## 31 33 3 0 3 970
## 32 34 3 0 3 1440
## 33 35 3 0 3 1010
## 34 36 3 60 3 730
## 35 37 3 60 3 240
## 36 38 3 840 3 2430
## 37 39 3 0 3 740
## 38 40 2 3340 3 840
## 39 41 2 4189 3 790
## 40 42 3 90 3 1410
## 41 43 3 0 3 2310
## 42 44 3 170 3 1460
## 43 45 3 60 3 1820
## 44 46 3 0 3 0
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## 48 50 3 680 3 1170
## 49 51 3 0 3 0
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## 51 53 3 530 3 670
## 52 54 2 3140 3 0
## 53 55 3 0 3 170
## 54 56 3 0 3 990
## 55 57 2 2870 3 620
## 56 58 3 150 3 1080
## 57 59 3 0 3 830
## 58 60 3 490 3 1200
## 59 61 3 0 3 1790
## 60 62 3 210 3 1130
## 61 63 2 2200 3 60
## 62 64 3 170 3 1500
## 63 65 3 0 2 3460
## 64 66 3 670 3 1000
## 65 67 2 1210 3 170
## 66 68 2 2960 3 650
## 67 69 3 170 3 600
## 68 70 3 860 3 900
## 69 71 3 0 3 660
## 70 72 3 20 3 2440
## 71 73 3 1180 3 1480
## 72 74 2 3160 3 430
## 73 75 3 430 3 1160
## 74 76 3 500 3 350
## 75 77 2 2180 3 60
## 76 78 3 0 3 260
## 77 79 3 140 3 970
## 78 80 NA NA NA NA
## 79 81 3 70 3 670
## 80 82 3 60 3 960
## 81 83 3 60 3 630
## 82 84 2 2870 2 3290
## 83 85 3 1000 3 1150
## 84 86 3 0 3 940
## 85 87 3 0 3 170
## 86 88 3 0 3 866
## 87 89 2 3280 3 820
## 88 90 2 3040 3 0
## SOFNoMusicEnemies SOFNoMusicFriendlies SOFNoMusicTime SOFMusicEnemies
## 1 22 2 24360 19
## 2 15 0 15300 23
## 3 3 0 5280 19
## 4 18 2 19140 23
## 5 23 1 23220 24
## 6 7 1 7740 20
## 7 17 1 20760 1
## 8 18 2 22800 16
## 9 16 2 19680 24
## 10 19 2 19260 26
## 11 23 1 23280 23
## 12 2 0 8040 23
## 13 29 0 23280 25
## 14 0 0 600 10
## 15 24 0 16200 26
## 16 0 0 0 15
## 17 19 1 22860 23
## 18 15 1 22140 21
## 19 21 1 22320 23
## 20 10 0 15240 14
## 21 21 0 23820 23
## 22 16 1 24000 15
## 23 25 0 22920 27
## 24 24 2 22920 24
## 25 1 0 4500 26
## 26 3 0 6540 1
## 27 10 0 21900 19
## 28 20 0 13380 26
## 29 2 0 11280 14
## 30 12 4 12840 12
## 31 15 0 11520 19
## 32 25 1 23520 NA
## 33 25 1 21900 23
## 34 18 1 23280 24
## 35 15 2 23760 7
## 36 24 1 21660 26
## 37 0 0 3660 0
## 38 20 1 22020 14
## 39 15 0 23460 25
## 40 19 1 22260 23
## 41 27 2 22080 30
## 42 24 1 18000 22
## 43 13 0 23340 23
## 44 1 0 6060 1
## 45 27 1 25380 28
## 46 2 0 5340 25
## 47 17 1 19440 24
## 48 17 2 20040 0
## 49 8 1 12900 NA
## 50 23 0 23880 23
## 51 25 0 24540 24
## 52 24 0 23700 23
## 53 11 0 9960 4
## 54 9 0 11040 17
## 55 24 0 23040 24
## 56 22 0 22020 26
## 57 23 2 23460 23
## 58 18 1 23040 26
## 59 21 0 23520 18
## 60 21 1 19740 23
## 61 1 0 4620 0
## 62 20 1 16200 13
## 63 13 2 19860 NA
## 64 8 0 7380 23
## 65 19 1 21600 27
## 66 21 1 22680 19
## 67 24 0 26760 25
## 68 16 0 19080 28
## 69 19 1 23280 26
## 70 16 1 11100 23
## 71 27 0 21480 36
## 72 24 2 24180 24
## 73 15 1 24240 11
## 74 6 1 12060 25
## 75 15 0 12720 25
## 76 2 0 6720 17
## 77 17 1 23400 20
## 78 NA NA NA NA
## 79 21 0 23220 27
## 80 20 1 17520 28
## 81 17 1 18180 26
## 82 7 0 17100 19
## 83 25 2 24420 30
## 84 19 2 24480 18
## 85 15 0 13140 25
## 86 24 0 23460 27
## 87 7 0 8880 31
## 88 22 2 28440 26
## SOFMusicFriendlies SOFMusicTime GameComments
## 1 0 23340
## 2 1 24300
## 3 0 16860 Participant died, restart
## 4 3 20820 Error in game towards the end of time
## 5 0 23400
## 6 2 23280 Participant died, restart
## 7 0 4980 Participant died, restart
## 8 2 23940
## 9 0 23100
## 10 0 18960
## 11 0 22980
## 12 1 21360 Participant died, restart
## 13 2 12540 Participant died, restart
## 14 0 12360 Participant died, restart
## 15 1 24480
## 16 2 17580 Participant died, restart
## 17 0 22440
## 18 1 13800 Participant died, restart
## 19 1 23160
## 20 0 23280
## 21 1 23340
## 22 0 23760
## 23 0 23520
## 24 1 22560
## 25 1 23460 Participant died, restart
## 26 0 4680 Participant died, restart
## 27 1 11700 Participant died, restart
## 28 0 23040 Participant died, restart
## 29 1 12240 Participant died, restart
## 30 0 10920 Participant died, restart
## 31 1 19440 Participant died, restart
## 32 NA NA No comments about blanks provided
## 33 1 23460
## 34 2 23640
## 35 0 8040 Participant died, restart
## 36 1 21360
## 37 0 4200 Participant died, restart
## 38 1 10260 Participant died, restart
## 39 0 15000
## 40 1 21060
## 41 1 21480
## 42 1 15900
## 43 0 24060
## 44 0 6060 Participant died, restart
## 45 0 18240
## 46 0 16380 Participant died, restart
## 47 0 23220
## 48 0 6720 Too many friendlies killed, restart
## 49 NA 22800 Too many friendlies killed, restart
## 50 1 22740
## 51 1 22020
## 52 0 22560
## 53 1 6720 Participant died, restart
## 54 1 12240 Participant died, restart
## 55 0 23100
## 56 1 22080
## 57 0 23280
## 58 1 22980
## 59 0 11100
## 60 2 19020
## 61 0 0 Participant died, restart
## 62 1 9720 Participant died, restart
## 63 NA NA Too many friendlies killed, restart
## 64 1 19620 Participant died, restart
## 65 0 22320
## 66 2 16380
## 67 1 23280
## 68 1 18840
## 69 0 23280
## 70 1 21780 Participant died, restart
## 71 0 24300
## 72 0 24540
## 73 0 8580 Participant died, restart
## 74 2 23640 Participant died, restart
## 75 2 22020 Participant died, restart
## 76 2 15600 Participant died, restart
## 77 1 12840 Participant died, restart
## 78 NA NA No comments about blanks provided
## 79 0 22980
## 80 0 22860
## 81 2 19080
## 82 0 19800
## 83 0 23460
## 84 1 23640
## 85 1 23160 Participant died, restart
## 86 0 22380
## 87 0 23100
## 88 0 25500
## DoNotUseVideoGamePerformanceData ConfrontationalAngryMusicScore
## 1 NA 5.500000
## 2 NA 5.333333
## 3 1 3.333333
## 4 1 6.000000
## 5 NA 5.500000
## 6 1 5.333333
## 7 1 4.666667
## 8 NA 2.166667
## 9 NA 6.000000
## 10 NA 4.166667
## 11 NA 5.000000
## 12 1 5.333333
## 13 1 3.833333
## 14 1 4.166667
## 15 NA 4.166667
## 16 1 4.833333
## 17 NA 6.500000
## 18 1 5.833333
## 19 NA 5.000000
## 20 NA 3.166667
## 21 NA 3.666667
## 22 NA 4.166667
## 23 NA 4.833333
## 24 NA 5.000000
## 25 1 5.500000
## 26 1 4.833333
## 27 1 6.500000
## 28 1 3.500000
## 29 1 3.833333
## 30 1 4.500000
## 31 1 6.000000
## 32 1 5.333333
## 33 NA 3.333333
## 34 NA 4.833333
## 35 1 4.666667
## 36 NA 3.166667
## 37 1 5.333333
## 38 1 5.500000
## 39 NA 5.500000
## 40 NA 6.166667
## 41 NA 5.000000
## 42 NA 5.166667
## 43 NA 5.166667
## 44 1 3.500000
## 45 NA 3.500000
## 46 1 4.333333
## 47 NA 5.500000
## 48 1 6.333333
## 49 1 5.000000
## 50 NA 4.000000
## 51 NA 6.166667
## 52 NA 5.000000
## 53 1 6.000000
## 54 1 3.333333
## 55 NA 3.500000
## 56 NA 5.000000
## 57 NA 7.000000
## 58 NA 5.333333
## 59 1 6.833333
## 60 1 4.833333
## 61 1 6.000000
## 62 1 5.666667
## 63 1 5.666667
## 64 1 5.666667
## 65 NA 1.833333
## 66 NA 5.833333
## 67 NA 6.666667
## 68 NA 5.000000
## 69 NA 4.500000
## 70 1 5.166667
## 71 NA 3.166667
## 72 NA 4.833333
## 73 1 5.000000
## 74 1 4.833333
## 75 1 5.000000
## 76 1 5.833333
## 77 1 3.500000
## 78 1 3.166667
## 79 NA 5.166667
## 80 NA 5.333333
## 81 NA 6.000000
## 82 NA 7.000000
## 83 NA 2.666667
## 84 NA 4.500000
## 85 1 4.166667
## 86 NA 6.166667
## 87 1 5.833333
## 88 NA 4.666667
## ConfrontationalExcitingMusicScore ConfrontationalNeutralMusicScore
## 1 3.333333 2.500000
## 2 3.000000 2.333333
## 3 3.500000 1.666667
## 4 1.833333 3.666667
## 5 2.666667 2.833333
## 6 1.500000 1.000000
## 7 3.333333 1.500000
## 8 2.000000 1.166667
## 9 4.666667 1.500000
## 10 1.666667 1.166667
## 11 4.500000 1.000000
## 12 2.166667 2.333333
## 13 1.833333 1.166667
## 14 4.333333 4.833333
## 15 2.000000 1.666667
## 16 1.166667 1.500000
## 17 2.833333 1.500000
## 18 2.666667 1.000000
## 19 1.333333 1.000000
## 20 3.833333 1.166667
## 21 2.166667 1.000000
## 22 2.833333 1.000000
## 23 3.500000 1.500000
## 24 3.500000 2.833333
## 25 2.666667 2.166667
## 26 1.000000 1.000000
## 27 3.000000 1.000000
## 28 2.500000 2.166667
## 29 4.333333 2.166667
## 30 2.166667 2.000000
## 31 1.833333 1.000000
## 32 5.000000 2.666667
## 33 3.166667 2.166667
## 34 2.166667 1.500000
## 35 1.000000 3.000000
## 36 1.833333 3.166667
## 37 1.166667 1.166667
## 38 4.000000 2.500000
## 39 2.666667 2.833333
## 40 2.833333 2.000000
## 41 2.166667 1.000000
## 42 4.166667 2.666667
## 43 3.833333 3.000000
## 44 5.000000 1.666667
## 45 1.166667 4.166667
## 46 2.666667 2.666667
## 47 2.666667 2.833333
## 48 3.000000 2.166667
## 49 3.000000 1.500000
## 50 2.500000 2.500000
## 51 3.666667 1.666667
## 52 1.000000 1.333333
## 53 3.166667 1.166667
## 54 2.333333 2.166667
## 55 2.333333 2.000000
## 56 1.166667 1.333333
## 57 2.833333 2.833333
## 58 2.666667 1.500000
## 59 2.000000 2.333333
## 60 3.000000 1.666667
## 61 1.000000 1.000000
## 62 2.500000 3.333333
## 63 2.333333 2.000000
## 64 1.500000 5.166667
## 65 2.333333 3.666667
## 66 3.500000 2.166667
## 67 3.333333 1.666667
## 68 1.000000 1.000000
## 69 2.666667 1.166667
## 70 2.166667 3.000000
## 71 4.333333 2.333333
## 72 1.833333 1.000000
## 73 2.333333 1.333333
## 74 1.333333 1.000000
## 75 1.833333 1.000000
## 76 3.833333 1.500000
## 77 1.333333 2.000000
## 78 1.000000 1.333333
## 79 2.500000 3.166667
## 80 2.166667 1.666667
## 81 2.166667 1.000000
## 82 2.333333 1.333333
## 83 1.333333 1.333333
## 84 2.500000 2.166667
## 85 1.666667 1.666667
## 86 4.833333 1.166667
## 87 2.500000 1.500000
## 88 1.666667 2.166667
## ConfrontationalAngryRecallScore ConfrontationalExcitingRecallScore
## 1 3.75 1.25
## 2 2.25 2.25
## 3 6.00 3.50
## 4 6.00 4.75
## 5 3.75 5.00
## 6 2.75 1.00
## 7 4.25 2.50
## 8 7.00 2.25
## 9 6.25 4.50
## 10 4.25 2.75
## 11 7.00 4.50
## 12 4.25 3.25
## 13 5.50 3.50
## 14 4.00 4.00
## 15 5.25 2.25
## 16 6.25 2.00
## 17 5.50 3.25
## 18 4.25 4.00
## 19 6.50 4.00
## 20 1.25 1.75
## 21 7.00 2.50
## 22 4.00 1.75
## 23 4.75 4.50
## 24 1.00 5.25
## 25 5.00 3.50
## 26 2.00 4.75
## 27 6.00 3.50
## 28 5.25 3.25
## 29 5.75 3.50
## 30 2.25 1.75
## 31 6.00 3.75
## 32 4.00 3.75
## 33 5.00 2.75
## 34 5.50 3.25
## 35 4.00 4.25
## 36 1.00 4.50
## 37 6.50 2.00
## 38 6.25 3.50
## 39 4.75 4.75
## 40 6.00 4.75
## 41 6.00 2.25
## 42 3.50 4.50
## 43 5.00 4.25
## 44 3.50 4.25
## 45 4.00 4.00
## 46 6.00 2.25
## 47 4.50 5.00
## 48 6.00 1.25
## 49 5.50 2.50
## 50 2.50 4.75
## 51 3.50 5.00
## 52 6.00 3.75
## 53 7.00 4.50
## 54 1.00 2.25
## 55 2.25 1.25
## 56 1.50 3.25
## 57 5.75 4.00
## 58 6.00 5.00
## 59 4.00 1.75
## 60 5.50 2.00
## 61 4.75 1.75
## 62 4.25 4.75
## 63 1.25 5.25
## 64 1.00 5.00
## 65 1.00 3.50
## 66 5.50 4.00
## 67 5.25 4.50
## 68 6.25 2.00
## 69 5.25 5.25
## 70 3.00 4.50
## 71 4.25 2.00
## 72 4.50 6.25
## 73 6.00 3.75
## 74 6.75 1.50
## 75 3.75 3.25
## 76 6.00 5.00
## 77 3.75 5.50
## 78 2.00 1.00
## 79 5.75 4.50
## 80 5.50 4.75
## 81 3.75 5.75
## 82 5.25 1.50
## 83 1.00 1.00
## 84 3.00 5.00
## 85 6.50 1.25
## 86 2.50 5.50
## 87 5.25 6.25
## 88 7.00 3.25
## ConfrontationalNeutralRecallScore NonconfrontationalAngryMusicScore
## 1 2.00 2.166667
## 2 2.25 2.666667
## 3 1.50 2.166667
## 4 1.75 4.000000
## 5 4.00 2.833333
## 6 3.50 1.666667
## 7 1.75 2.500000
## 8 3.50 3.666667
## 9 2.00 5.000000
## 10 1.50 2.333333
## 11 3.00 2.166667
## 12 2.00 3.666667
## 13 2.00 4.666667
## 14 3.25 2.166667
## 15 1.75 2.166667
## 16 1.75 2.833333
## 17 2.75 4.166667
## 18 1.25 2.166667
## 19 2.00 3.000000
## 20 1.00 1.500000
## 21 2.00 3.333333
## 22 1.00 2.000000
## 23 2.00 3.000000
## 24 6.50 3.000000
## 25 2.50 2.000000
## 26 2.00 3.166667
## 27 1.75 3.333333
## 28 2.50 1.500000
## 29 2.75 3.000000
## 30 1.75 3.333333
## 31 2.00 3.666667
## 32 3.50 3.166667
## 33 3.75 3.500000
## 34 2.00 3.500000
## 35 4.25 3.333333
## 36 5.00 1.500000
## 37 2.00 2.333333
## 38 3.00 5.000000
## 39 1.50 5.000000
## 40 2.00 3.166667
## 41 1.00 2.833333
## 42 4.25 4.833333
## 43 3.25 3.000000
## 44 2.25 3.666667
## 45 4.00 3.666667
## 46 3.00 3.666667
## 47 4.00 3.166667
## 48 1.75 1.833333
## 49 1.50 3.500000
## 50 4.25 3.000000
## 51 3.25 2.500000
## 52 2.75 1.833333
## 53 1.00 4.166667
## 54 2.50 1.666667
## 55 1.00 2.833333
## 56 3.25 4.000000
## 57 2.00 4.333333
## 58 1.25 3.500000
## 59 1.25 2.833333
## 60 2.75 3.500000
## 61 2.75 3.166667
## 62 4.75 3.833333
## 63 4.00 1.166667
## 64 3.75 3.500000
## 65 3.00 2.333333
## 66 2.25 4.833333
## 67 2.50 3.500000
## 68 1.00 1.666667
## 69 2.00 2.000000
## 70 1.25 4.500000
## 71 2.25 5.000000
## 72 3.50 3.166667
## 73 1.75 2.333333
## 74 2.00 2.666667
## 75 2.00 2.666667
## 76 3.00 3.833333
## 77 2.75 2.666667
## 78 1.00 1.833333
## 79 4.50 3.500000
## 80 2.00 4.000000
## 81 1.50 3.833333
## 82 1.00 2.500000
## 83 1.00 3.166667
## 84 1.75 3.333333
## 85 1.75 3.666667
## 86 4.50 3.333333
## 87 2.25 2.166667
## 88 1.00 2.000000
## NonconfrontationalExcitingMusicScore NonconfrontationalNeutralMusicScore
## 1 3.166667 4.000000
## 2 4.500000 2.833333
## 3 4.166667 3.500000
## 4 3.000000 3.666667
## 5 2.333333 4.333333
## 6 3.833333 3.666667
## 7 3.666667 2.333333
## 8 3.166667 2.500000
## 9 4.166667 2.166667
## 10 2.166667 2.500000
## 11 4.666667 2.500000
## 12 3.000000 3.166667
## 13 3.666667 3.500000
## 14 4.333333 6.833333
## 15 2.333333 3.000000
## 16 4.000000 5.000000
## 17 1.500000 2.500000
## 18 3.833333 4.166667
## 19 3.500000 3.833333
## 20 3.166667 1.833333
## 21 3.166667 2.000000
## 22 2.166667 3.500000
## 23 3.666667 6.333333
## 24 3.166667 6.000000
## 25 3.666667 3.166667
## 26 3.833333 1.000000
## 27 2.166667 3.833333
## 28 2.666667 5.833333
## 29 3.500000 3.500000
## 30 2.666667 3.000000
## 31 3.666667 2.833333
## 32 5.166667 5.333333
## 33 3.833333 3.333333
## 34 3.666667 3.833333
## 35 4.666667 4.833333
## 36 1.166667 4.833333
## 37 1.666667 3.333333
## 38 4.666667 3.333333
## 39 2.166667 4.000000
## 40 5.000000 2.500000
## 41 4.000000 3.166667
## 42 2.333333 3.000000
## 43 4.333333 4.333333
## 44 2.666667 3.000000
## 45 2.000000 4.000000
## 46 2.166667 4.833333
## 47 3.166667 3.500000
## 48 3.666667 6.000000
## 49 3.500000 3.833333
## 50 4.666667 4.666667
## 51 5.000000 3.666667
## 52 3.500000 4.500000
## 53 3.333333 3.666667
## 54 1.666667 2.166667
## 55 3.333333 4.333333
## 56 2.666667 1.833333
## 57 3.666667 4.166667
## 58 4.000000 3.000000
## 59 3.666667 5.666667
## 60 3.666667 2.000000
## 61 3.666667 2.166667
## 62 4.000000 4.666667
## 63 3.000000 3.166667
## 64 2.833333 4.833333
## 65 1.500000 3.166667
## 66 3.833333 2.500000
## 67 4.000000 3.666667
## 68 3.833333 4.000000
## 69 1.333333 5.166667
## 70 3.666667 2.666667
## 71 4.833333 2.000000
## 72 3.000000 2.166667
## 73 2.666667 2.666667
## 74 1.833333 2.000000
## 75 2.166667 3.166667
## 76 5.833333 3.333333
## 77 1.833333 5.333333
## 78 2.166667 4.000000
## 79 2.666667 3.833333
## 80 4.000000 3.333333
## 81 3.666667 1.500000
## 82 4.000000 3.166667
## 83 2.000000 1.666667
## 84 3.500000 2.166667
## 85 2.500000 3.666667
## 86 1.833333 3.500000
## 87 5.333333 4.000000
## 88 2.500000 3.833333
## NonconfrontationalAngryRecallScore NonconfrontationalExcitingRecallScore
## 1 2.50 5.25
## 2 4.25 4.25
## 3 3.75 5.00
## 4 2.00 5.75
## 5 1.25 3.50
## 6 1.00 6.25
## 7 1.75 5.75
## 8 3.00 4.00
## 9 2.00 4.25
## 10 2.50 6.00
## 11 2.50 5.25
## 12 3.25 5.25
## 13 1.75 4.75
## 14 1.00 7.00
## 15 2.50 4.50
## 16 4.25 3.50
## 17 3.50 4.00
## 18 1.00 4.00
## 19 1.75 4.75
## 20 1.00 4.00
## 21 1.00 7.00
## 22 1.00 4.25
## 23 4.00 3.50
## 24 1.00 4.25
## 25 1.25 3.50
## 26 2.25 5.50
## 27 1.00 5.25
## 28 1.75 4.00
## 29 3.75 4.50
## 30 2.25 5.00
## 31 1.25 3.50
## 32 2.50 5.25
## 33 1.00 5.75
## 34 2.25 5.00
## 35 3.50 4.00
## 36 1.00 4.25
## 37 2.75 4.25
## 38 3.25 4.50
## 39 3.75 5.75
## 40 2.50 5.50
## 41 1.25 5.75
## 42 3.50 5.00
## 43 3.50 3.75
## 44 3.00 4.75
## 45 4.00 4.00
## 46 3.25 7.00
## 47 2.75 5.50
## 48 1.00 5.50
## 49 1.75 5.50
## 50 2.00 5.25
## 51 2.25 6.25
## 52 1.00 6.25
## 53 2.25 4.75
## 54 2.00 2.25
## 55 1.75 3.25
## 56 2.00 2.25
## 57 1.50 6.25
## 58 1.00 4.25
## 59 1.00 5.50
## 60 2.50 6.25
## 61 1.25 6.00
## 62 2.25 4.50
## 63 1.75 4.50
## 64 1.00 3.25
## 65 1.00 4.75
## 66 4.00 5.75
## 67 1.00 3.50
## 68 1.00 6.50
## 69 1.50 4.00
## 70 2.00 5.25
## 71 1.00 5.75
## 72 1.25 7.00
## 73 1.50 5.00
## 74 1.25 5.00
## 75 1.00 5.75
## 76 2.75 5.25
## 77 3.50 6.00
## 78 1.00 4.75
## 79 4.00 5.00
## 80 3.00 5.25
## 81 1.00 6.00
## 82 1.00 4.50
## 83 2.00 3.50
## 84 2.25 4.75
## 85 1.25 4.25
## 86 1.75 6.00
## 87 1.00 4.25
## 88 2.25 7.00
## NonconfrontationalNeutralRecallScore ConfrontationalAngerScore
## 1 6.25 4.8
## 2 3.25 4.1
## 3 2.00 4.4
## 4 5.00 6.0
## 5 3.75 4.8
## 6 5.50 4.3
## 7 4.75 4.5
## 8 3.50 4.1
## 9 3.00 6.1
## 10 3.75 4.2
## 11 6.50 5.8
## 12 3.25 4.9
## 13 4.00 4.5
## 14 7.00 4.1
## 15 5.00 4.6
## 16 2.00 5.4
## 17 4.50 6.1
## 18 4.25 5.2
## 19 4.75 5.6
## 20 4.25 2.4
## 21 4.00 5.0
## 22 2.50 4.1
## 23 3.50 4.8
## 24 6.75 3.4
## 25 5.25 5.3
## 26 3.00 3.7
## 27 4.25 6.3
## 28 5.50 4.2
## 29 2.75 4.6
## 30 4.25 3.6
## 31 5.50 6.0
## 32 5.25 4.8
## 33 5.75 4.0
## 34 5.00 5.1
## 35 3.75 4.4
## 36 5.50 2.3
## 37 2.50 5.8
## 38 3.75 5.8
## 39 5.25 5.2
## 40 4.00 6.1
## 41 4.50 5.4
## 42 4.75 4.5
## 43 4.75 5.1
## 44 2.75 3.5
## 45 4.00 3.7
## 46 5.75 5.0
## 47 4.75 5.1
## 48 4.00 6.2
## 49 4.25 5.2
## 50 4.75 3.4
## 51 5.25 5.1
## 52 3.75 5.4
## 53 4.75 6.4
## 54 3.25 2.4
## 55 4.25 3.0
## 56 1.75 3.6
## 57 3.75 6.5
## 58 4.25 5.6
## 59 3.50 5.7
## 60 3.25 5.1
## 61 4.00 5.5
## 62 5.25 5.1
## 63 3.75 3.9
## 64 6.25 3.8
## 65 2.25 1.5
## 66 5.00 5.7
## 67 4.00 6.1
## 68 2.50 5.5
## 69 6.25 4.8
## 70 3.50 4.3
## 71 3.50 3.6
## 72 4.75 4.7
## 73 3.50 5.4
## 74 6.00 5.6
## 75 5.00 4.5
## 76 4.25 5.9
## 77 3.50 3.6
## 78 3.75 2.7
## 79 5.25 5.4
## 80 2.75 5.4
## 81 6.50 5.1
## 82 5.50 6.3
## 83 2.25 2.0
## 84 3.75 3.9
## 85 5.75 5.1
## 86 5.50 4.7
## 87 5.25 5.6
## 88 6.00 5.6
## ConfrontationalExcitingScore ConfrontationalNeutralScore
## 1 2.5 2.3
## 2 2.7 2.3
## 3 3.5 1.6
## 4 3.0 2.9
## 5 3.6 3.3
## 6 1.3 2.0
## 7 3.0 1.6
## 8 2.1 2.1
## 9 4.6 1.7
## 10 2.1 1.3
## 11 4.5 1.8
## 12 2.6 2.2
## 13 2.5 1.5
## 14 4.2 4.2
## 15 2.1 1.7
## 16 1.5 1.6
## 17 3.0 2.0
## 18 3.2 1.1
## 19 2.4 1.4
## 20 3.0 1.1
## 21 2.3 1.4
## 22 2.4 1.0
## 23 3.9 1.7
## 24 4.2 4.3
## 25 3.0 2.3
## 26 2.5 1.4
## 27 3.2 1.3
## 28 2.8 2.3
## 29 4.0 2.4
## 30 2.0 1.9
## 31 2.6 1.4
## 32 4.5 3.0
## 33 3.0 2.8
## 34 2.6 1.7
## 35 2.3 3.5
## 36 2.9 3.9
## 37 1.5 1.5
## 38 3.8 2.7
## 39 3.5 2.3
## 40 3.6 2.0
## 41 2.2 1.0
## 42 4.3 3.3
## 43 4.0 3.1
## 44 4.7 1.9
## 45 2.3 4.1
## 46 2.5 2.8
## 47 3.6 3.3
## 48 2.3 2.0
## 49 2.8 1.5
## 50 3.4 3.2
## 51 4.2 2.3
## 52 2.1 1.9
## 53 3.7 1.1
## 54 2.3 2.3
## 55 1.9 1.6
## 56 2.0 2.1
## 57 3.3 2.5
## 58 3.6 1.4
## 59 1.9 1.9
## 60 2.6 2.1
## 61 1.3 1.7
## 62 3.4 3.9
## 63 3.5 2.8
## 64 2.9 4.6
## 65 2.8 3.4
## 66 3.7 2.2
## 67 3.8 2.0
## 68 1.4 1.0
## 69 3.7 1.5
## 70 3.1 2.3
## 71 3.4 2.3
## 72 3.6 2.0
## 73 2.9 1.5
## 74 1.4 1.4
## 75 2.4 1.4
## 76 4.3 2.1
## 77 3.0 2.3
## 78 1.0 1.2
## 79 3.3 3.7
## 80 3.2 1.8
## 81 3.6 1.2
## 82 2.0 1.2
## 83 1.2 1.2
## 84 3.5 2.0
## 85 1.5 1.7
## 86 5.1 2.5
## 87 4.0 1.8
## 88 2.3 1.7
## NonconfrontationalAngerScore NonconfrontationalExcitingScore
## 1 2.3 4.0
## 2 3.3 4.4
## 3 2.8 4.5
## 4 3.2 4.1
## 5 2.2 2.8
## 6 1.4 4.8
## 7 2.2 4.5
## 8 3.4 3.5
## 9 3.8 4.2
## 10 2.4 3.7
## 11 2.3 4.9
## 12 3.5 3.9
## 13 3.5 4.1
## 14 1.7 5.4
## 15 2.3 3.2
## 16 3.4 3.8
## 17 3.9 2.5
## 18 1.7 3.9
## 19 2.5 4.0
## 20 1.3 3.5
## 21 2.4 4.7
## 22 1.6 3.0
## 23 3.4 3.6
## 24 2.2 3.6
## 25 1.7 3.6
## 26 2.8 4.5
## 27 2.4 3.4
## 28 1.6 3.2
## 29 3.3 3.9
## 30 2.9 3.6
## 31 2.7 3.6
## 32 2.9 5.2
## 33 2.5 4.6
## 34 3.0 4.2
## 35 3.4 4.4
## 36 1.3 2.4
## 37 2.5 2.7
## 38 4.3 4.6
## 39 4.5 3.6
## 40 2.9 5.2
## 41 2.2 4.7
## 42 4.3 3.4
## 43 3.2 4.1
## 44 3.4 3.5
## 45 3.8 2.8
## 46 3.5 4.1
## 47 3.0 4.1
## 48 1.5 4.4
## 49 2.8 4.3
## 50 2.6 4.9
## 51 2.4 5.5
## 52 1.5 4.6
## 53 3.4 3.9
## 54 1.8 1.9
## 55 2.4 3.3
## 56 3.2 2.5
## 57 3.2 4.7
## 58 2.5 4.1
## 59 2.1 4.4
## 60 3.1 4.7
## 61 2.4 4.6
## 62 3.2 4.2
## 63 1.4 3.6
## 64 2.5 3.0
## 65 1.8 2.8
## 66 4.5 4.6
## 67 2.5 3.8
## 68 1.4 4.9
## 69 1.8 2.4
## 70 3.5 4.3
## 71 3.4 5.2
## 72 2.4 4.6
## 73 2.0 3.6
## 74 2.1 3.1
## 75 2.0 3.6
## 76 3.4 5.6
## 77 3.0 3.5
## 78 1.5 3.2
## 79 3.7 3.6
## 80 3.6 4.5
## 81 2.7 4.6
## 82 1.9 4.2
## 83 2.7 2.6
## 84 2.9 4.0
## 85 2.7 3.2
## 86 2.7 3.5
## 87 1.7 4.9
## 88 2.1 4.3
## NonconfrontationalNeutralScore Usable DoNotUse
## 1 4.9 1 NA
## 2 3.0 1 NA
## 3 2.9 1 NA
## 4 4.2 1 NA
## 5 4.1 1 NA
## 6 4.4 1 NA
## 7 3.3 1 NA
## 8 2.9 1 NA
## 9 2.5 1 NA
## 10 3.0 1 NA
## 11 4.1 1 NA
## 12 3.2 1 NA
## 13 3.7 1 NA
## 14 6.9 1 NA
## 15 3.8 1 NA
## 16 3.8 1 NA
## 17 3.3 1 NA
## 18 4.2 1 NA
## 19 4.2 1 NA
## 20 2.8 1 NA
## 21 2.8 1 NA
## 22 3.1 1 NA
## 23 5.2 1 NA
## 24 6.3 1 NA
## 25 4.0 1 NA
## 26 1.8 1 NA
## 27 4.0 1 NA
## 28 5.7 1 NA
## 29 3.2 1 NA
## 30 3.5 1 NA
## 31 3.9 1 NA
## 32 5.3 1 NA
## 33 4.3 1 NA
## 34 4.3 1 NA
## 35 4.4 1 NA
## 36 5.1 1 NA
## 37 3.0 1 NA
## 38 3.5 1 NA
## 39 4.5 1 NA
## 40 3.1 1 NA
## 41 3.7 1 NA
## 42 3.7 1 NA
## 43 4.5 1 NA
## 44 2.9 1 NA
## 45 4.0 1 NA
## 46 5.2 1 NA
## 47 4.0 1 NA
## 48 5.2 1 NA
## 49 4.0 1 NA
## 50 4.7 1 NA
## 51 4.3 1 NA
## 52 4.2 1 NA
## 53 4.1 1 NA
## 54 2.6 1 NA
## 55 4.3 1 NA
## 56 1.8 1 NA
## 57 4.0 1 NA
## 58 3.5 1 NA
## 59 4.8 1 NA
## 60 2.5 1 NA
## 61 2.9 1 NA
## 62 4.9 1 NA
## 63 3.4 1 NA
## 64 5.4 1 NA
## 65 2.8 1 NA
## 66 3.5 1 NA
## 67 3.8 1 NA
## 68 3.4 1 NA
## 69 5.6 1 NA
## 70 3.0 1 NA
## 71 2.6 1 NA
## 72 3.2 1 NA
## 73 3.0 1 NA
## 74 3.6 1 NA
## 75 3.9 1 NA
## 76 3.7 1 NA
## 77 4.6 1 NA
## 78 3.9 1 NA
## 79 4.4 1 NA
## 80 3.1 1 NA
## 81 3.5 1 NA
## 82 4.1 1 NA
## 83 1.9 1 NA
## 84 2.8 1 NA
## 85 4.5 1 NA
## 86 4.3 1 NA
## 87 4.5 1 NA
## 88 4.7 1 NA
## ProblemDetails
## 1
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
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## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32
## 33
## 34
## 35
## 36
## 37
## 38
## 39
## 40
## 41
## 42
## 43
## 44
## 45
## 46
## 47
## 48
## 49
## 50
## 51
## 52
## 53
## 54
## 55
## 56
## 57
## 58
## 59
## 60
## 61
## 62
## 63
## 64
## 65
## 66
## 67
## 68
## 69
## 70
## 71
## 72
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## 75
## 76
## 77
## 78
## 79
## 80
## 81
## 82
## 83
## 84
## 85
## 86
## 87
## 88
## DinerDashWithMusicScore DinerDashWithoutMusicScore MusicCondition
## 1 5830 5000 Exciting
## 2 5370 1250 Anger
## 3 6921 6742 Anger
## 4 6750 5060 Exciting
## 5 6380 5840 Neutral
## 6 5170 5020 Neutral
## 7 5690 5000 Neutral
## 8 6440 6460 Exciting
## 9 5480 2990 Anger
## 10 6210 5090 Exciting
## 11 6270 5490 Anger
## 12 6150 5140 Anger
## 13 7440 NA Neutral
## 14 5660 5000 Exciting
## 15 6810 5200 Neutral
## 16 5950 3040 Exciting
## 17 6160 5140 Anger
## 18 6240 5370 Anger
## 19 6650 5170 Neutral
## 20 6500 3000 Neutral
## 21 5770 5000 Exciting
## 22 5950 5060 Exciting
## 23 5550 5000 Exciting
## 24 6560 5020 Anger
## 25 6190 5370 Neutral
## 26 5930 5000 Anger
## 27 5990 5000 Neutral
## 28 6160 5960 Exciting
## 29 5020 970 Anger
## 30 5000 1090 Exciting
## 31 5970 5000 Neutral
## 32 6440 5000 Anger
## 33 6010 5000 Exciting
## 34 5730 5060 Neutral
## 35 5240 5060 Anger
## 36 7430 5840 Neutral
## 37 5740 5000 Anger
## 38 5840 3340 Neutral
## 39 5790 4189 Exciting
## 40 6410 5090 Exciting
## 41 7310 5000 Neutral
## 42 6460 5170 Exciting
## 43 6820 5060 Neutral
## 44 5000 5000 Anger
## 45 5100 5000 Anger
## 46 6100 5000 Exciting
## 47 5920 5370 Exciting
## 48 6170 5680 Neutral
## 49 5000 5000 Anger
## 50 5990 5000 Anger
## 51 5670 5530 Neutral
## 52 5000 3140 Exciting
## 53 5170 5000 Anger
## 54 5990 5000 Neutral
## 55 5620 2870 Exciting
## 56 6080 5150 Exciting
## 57 5830 5000 Anger
## 58 6200 5490 Neutral
## 59 6790 5000 Neutral
## 60 6130 5210 Neutral
## 61 5060 2200 Anger
## 62 6500 5170 Exciting
## 63 3460 5000 Anger
## 64 6000 5670 Exciting
## 65 5170 1210 Anger
## 66 5650 2960 Neutral
## 67 5600 5170 Neutral
## 68 5900 5860 Exciting
## 69 5660 5000 Exciting
## 70 7440 5020 Anger
## 71 6480 6180 Anger
## 72 5430 3160 Exciting
## 73 6160 5430 Neutral
## 74 5350 5500 Exciting
## 75 5060 2180 Anger
## 76 5260 5000 Neutral
## 77 5970 5140 Neutral
## 78 NA NA Exciting
## 79 5670 5070 Exciting
## 80 5960 5060 Neutral
## 81 5630 5060 Anger
## 82 3290 2870 Anger
## 83 6150 6000 Exciting
## 84 5940 5000 Neutral
## 85 5170 5000 Anger
## 86 5866 5000 Neutral
## 87 5820 3280 Exciting
## 88 5000 3040 Neutral
## ZDinerDashWithMusicScore ZDinerDashWithoutMusicScore ZSOFNoMusicEnemies
## 1 -0.07333283 0.2692740 0.75011992
## 2 -0.73344247 -2.8616517 -0.14019582
## 3 1.49227504 1.7236934 -1.66645139
## 4 1.24688645 0.3193688 0.24136807
## 5 0.71592870 0.9706014 0.87730789
## 6 -1.02044667 0.2859723 -1.15769954
## 7 -0.27423577 0.2692740 0.11418010
## 8 0.80202995 1.4882478 0.24136807
## 9 -0.57559017 -1.4089022 -0.01300786
## 10 0.47197513 0.3444162 0.36855603
## 11 0.55807639 0.6783816 0.87730789
## 12 0.38587388 0.3861619 -1.79363936
## 13 2.23705091 NA 1.64043567
## 14 -0.31728640 0.2692740 -2.04801529
## 15 1.33298771 0.4362567 1.00449585
## 16 0.09886968 -1.3671565 -2.04801529
## 17 0.40022408 0.3861619 0.36855603
## 18 0.51502576 0.5781920 -0.14019582
## 19 1.10338436 0.4112093 0.62293196
## 20 0.88813121 -1.4005530 -0.77613564
## 21 -0.15943409 0.2692740 0.62293196
## 22 0.09886968 0.3193688 -0.01300786
## 23 -0.47513870 0.2692740 1.13168382
## 24 0.97423247 0.2859723 1.00449585
## 25 0.44327471 0.5781920 -1.92082732
## 26 0.07016926 0.2692740 -1.66645139
## 27 0.15627052 0.2692740 -0.77613564
## 28 0.40022408 1.0707910 0.49574400
## 29 -1.23569981 -3.0954275 -1.79363936
## 30 -1.26440023 -2.9952379 -0.52175972
## 31 0.12757010 0.2692740 -0.14019582
## 32 0.80202995 0.2692740 1.13168382
## 33 0.18497094 0.2692740 1.13168382
## 34 -0.21683493 0.3193688 0.24136807
## 35 -0.91999520 0.3193688 -0.14019582
## 36 2.22270071 0.9706014 1.00449585
## 37 -0.20248472 0.2692740 -2.04801529
## 38 -0.05898262 -1.1166824 0.49574400
## 39 -0.13073367 -0.4078409 -0.14019582
## 40 0.75897932 0.3444162 0.36855603
## 41 2.05049819 0.2692740 1.38605975
## 42 0.83073037 0.4112093 1.00449585
## 43 1.34733792 0.3193688 -0.39457175
## 44 -1.26440023 0.2692740 -1.92082732
## 45 -1.12089813 0.2692740 1.38605975
## 46 0.31412283 0.2692740 -1.79363936
## 47 0.05581905 0.5781920 0.11418010
## 48 0.41457429 0.8370152 0.11418010
## 49 -1.26440023 0.2692740 -1.03051157
## 50 0.15627052 0.2692740 0.87730789
## 51 -0.30293619 0.7117782 1.13168382
## 52 -1.26440023 -1.2836652 1.00449585
## 53 -1.02044667 0.2692740 -0.64894768
## 54 0.15627052 0.2692740 -0.90332361
## 55 -0.37468723 -1.5090918 1.00449585
## 56 0.28542241 0.3945110 0.75011992
## 57 -0.07333283 0.2692740 0.87730789
## 58 0.45762492 0.6783816 0.24136807
## 59 1.30428729 0.2692740 0.62293196
## 60 0.35717346 0.4446058 0.62293196
## 61 -1.17829897 -2.0684839 -1.92082732
## 62 0.88813121 0.4112093 0.49574400
## 63 -3.47433251 0.2692740 -0.39457175
## 64 0.17062073 0.8286661 -1.03051157
## 65 -1.02044667 -2.8950483 0.36855603
## 66 -0.33163661 -1.4339496 0.62293196
## 67 -0.40338765 0.4112093 1.00449585
## 68 0.02711863 0.9872996 -0.01300786
## 69 -0.31728640 0.2692740 0.36855603
## 70 2.23705091 0.2859723 -0.01300786
## 71 0.85943079 1.2544720 1.38605975
## 72 -0.64734122 -1.2669669 1.00449585
## 73 0.40022408 0.6282868 -0.14019582
## 74 -0.76214289 0.6867308 -1.28488750
## 75 -1.17829897 -2.0851821 -0.14019582
## 76 -0.89129478 0.2692740 -1.79363936
## 77 0.12757010 0.3861619 0.11418010
## 78 NA NA NA
## 79 -0.30293619 0.3277180 0.62293196
## 80 0.11321989 0.3193688 0.49574400
## 81 -0.36033702 0.3193688 0.11418010
## 82 -3.71828607 -1.5090918 -1.15769954
## 83 0.38587388 1.1041875 1.13168382
## 84 0.08451947 0.2692740 0.36855603
## 85 -1.02044667 0.2692740 -0.14019582
## 86 -0.02167208 0.2692740 1.00449585
## 87 -0.08768304 -1.1667773 -1.15769954
## 88 -1.26440023 -1.3671565 0.75011992
## ZSOFMusicEnemies DinerDashDifferenceScore SOFDifferenceScore
## 1 -0.20203285 -0.3426068400 -0.95215278
## 2 0.31835480 2.1282092433 0.45855062
## 3 -0.20203285 -0.2314183350 1.46441854
## 4 0.31835480 0.9275176327 0.07698673
## 5 0.44845171 -0.2546726738 -0.42885618
## 6 -0.07193594 -1.3064189449 1.08576360
## 7 -2.54377728 -0.5435097745 -2.65795739
## 8 -0.59232359 -0.6862178028 -0.83369166
## 9 0.44845171 0.8333120125 0.46145957
## 10 0.70864554 0.1275589079 0.34008950
## 11 0.31835480 -0.1203052452 -0.55895309
## 12 0.31835480 -0.0002880261 2.11199416
## 13 0.57854862 NA -1.06188705
## 14 -1.37290507 -0.5865604034 0.67511022
## 15 0.70864554 0.8967309966 -0.29585032
## 16 -0.72242050 1.4660261879 1.32559478
## 17 0.31835480 0.0140621835 -0.05020123
## 18 0.05816097 -0.0631662508 0.19835680
## 19 0.31835480 0.6921750486 -0.30457716
## 20 -0.85251742 2.2886842576 -0.07638177
## 21 0.31835480 -0.4287080977 -0.30457716
## 22 -0.72242050 -0.2204991362 -0.70941264
## 23 0.83874245 -0.7444127091 -0.29294137
## 24 0.44845171 0.6882601912 -0.55604414
## 25 0.70864554 -0.1349172989 2.62947286
## 26 -2.54377728 -0.1991047439 -0.87732589
## 27 -0.20203285 -0.1130034862 0.57410279
## 28 0.70864554 -0.6705669085 0.21290154
## 29 -0.85251742 1.8597276944 0.94112194
## 30 -1.11271124 1.7308376520 -0.59095153
## 31 -0.20203285 -0.1417039054 -0.06183703
## 32 NA 0.5327559463 NA
## 33 0.31835480 -0.0843030670 -0.81332902
## 34 0.44845171 -0.5362037477 0.20708364
## 35 -1.76319581 -1.2393640187 -1.62299998
## 36 0.70864554 1.2520993354 -0.29585032
## 37 -2.67387419 -0.4717587265 -0.62585891
## 38 -0.85251742 1.0576998241 -1.34826141
## 39 0.57854862 0.2771071918 0.71874445
## 40 0.31835480 0.4145631001 -0.05020123
## 41 1.22903319 1.7812241826 -0.15702656
## 42 0.18825789 0.4195210660 -0.81623797
## 43 0.31835480 1.0279691000 0.71292655
## 44 -2.54377728 -1.5336742378 -0.62294996
## 45 0.96883936 -1.3901721417 -0.41722038
## 46 0.57854862 0.0448488195 2.37218798
## 47 0.44845171 -0.5223729584 0.33427161
## 48 -2.67387419 -0.4224409114 -2.78805430
## 49 NA -1.5336742378 NA
## 50 0.31835480 -0.1130034862 -0.55895309
## 51 0.44845171 -1.0147143630 -0.68323211
## 52 0.31835480 0.0192649221 -0.68614105
## 53 -2.15348654 -1.2897206744 -1.50453886
## 54 -0.46222668 -0.1130034862 0.44109693
## 55 0.44845171 1.1344045702 -0.55604414
## 56 0.70864554 -0.1090886287 -0.04147439
## 57 0.31835480 -0.3426068400 -0.55895309
## 58 0.70864554 -0.2207567125 0.46727747
## 59 -0.33212977 1.0350132828 -0.95506173
## 60 0.31835480 -0.0874323922 -0.30457716
## 61 -2.67387419 0.8901848949 -0.75304687
## 62 -0.98261433 0.4769219045 -1.47835833
## 63 NA -3.7436065180 NA
## 64 0.31835480 -0.6580453395 1.34886637
## 65 0.83874245 1.8746015922 0.47018642
## 66 -0.20203285 1.1023129817 -0.82496481
## 67 0.57854862 -0.8145969606 -0.42594723
## 68 0.96883936 -0.9601810057 0.98184722
## 69 0.70864554 -0.5865604034 0.34008950
## 70 0.31835480 1.9510786370 0.33136266
## 71 2.00961466 -0.3950411768 0.62355492
## 72 0.44845171 0.6196256648 -0.55604414
## 73 -1.24280815 -0.2280627393 -1.10261233
## 74 0.57854862 -1.4488736648 1.86343612
## 75 0.57854862 0.9068831655 0.71874445
## 76 -0.46222668 -1.1605687879 1.33141268
## 77 -0.07193594 -0.2585917992 -0.18611604
## 78 NA NA NA
## 79 0.83874245 -0.6306541406 0.21581049
## 80 0.96883936 -0.2061489266 0.47309537
## 81 0.70864554 -0.6797058438 0.59446543
## 82 -0.20203285 -2.2091942693 0.95566668
## 83 1.22903319 -0.7183136592 0.09734937
## 84 -0.33212977 -0.1847545342 -0.70068580
## 85 0.57854862 -1.2897206744 0.71874445
## 86 0.83874245 -0.2909460854 -0.16575340
## 87 1.35913010 1.0790942165 2.51682964
## 88 0.70864554 0.1027562747 -0.04147439
## PleasantScoreForAngryMusic PleasantScoreForExcitingMusic
## 1 1.333333 1.666667
## 2 2.666667 2.000000
## 3 1.666667 3.666667
## 4 3.000000 1.333333
## 5 2.333333 3.333333
## 6 1.666667 3.333333
## 7 1.666667 2.000000
## 8 2.333333 2.666667
## 9 2.333333 3.333333
## 10 1.333333 2.000000
## 11 2.000000 2.333333
## 12 2.000000 2.000000
## 13 2.333333 2.000000
## 14 1.333333 2.333333
## 15 1.333333 1.000000
## 16 3.666667 2.666667
## 17 3.000000 2.333333
## 18 1.666667 3.666667
## 19 2.000000 1.333333
## 20 1.333333 3.000000
## 21 2.333333 2.000000
## 22 1.333333 1.666667
## 23 1.666667 3.666667
## 24 2.000000 3.000000
## 25 2.000000 1.666667
## 26 1.333333 2.666667
## 27 1.333333 1.666667
## 28 1.000000 1.666667
## 29 3.000000 3.000000
## 30 1.666667 1.666667
## 31 1.333333 3.333333
## 32 2.000000 2.333333
## 33 3.333333 3.666667
## 34 2.333333 3.666667
## 35 2.666667 4.000000
## 36 3.000000 3.333333
## 37 2.000000 3.000000
## 38 1.333333 1.000000
## 39 3.333333 2.333333
## 40 2.333333 4.000000
## 41 1.000000 1.000000
## 42 3.666667 3.000000
## 43 2.000000 3.000000
## 44 1.000000 2.333333
## 45 2.666667 3.000000
## 46 4.000000 5.000000
## 47 2.000000 3.000000
## 48 3.333333 2.333333
## 49 1.333333 2.333333
## 50 2.000000 2.666667
## 51 1.666667 3.000000
## 52 1.666667 4.000000
## 53 2.333333 2.333333
## 54 1.000000 2.666667
## 55 2.000000 2.333333
## 56 1.333333 2.666667
## 57 3.333333 2.666667
## 58 2.000000 4.333333
## 59 1.666667 3.000000
## 60 1.333333 3.666667
## 61 2.000000 4.666667
## 62 1.666667 3.000000
## 63 1.000000 1.000000
## 64 2.333333 3.666667
## 65 1.666667 2.333333
## 66 1.333333 1.333333
## 67 1.666667 3.000000
## 68 2.333333 2.666667
## 69 1.666667 2.333333
## 70 3.000000 1.666667
## 71 1.666667 4.666667
## 72 3.333333 4.666667
## 73 1.333333 2.333333
## 74 2.000000 2.333333
## 75 1.000000 2.333333
## 76 1.666667 4.333333
## 77 4.000000 4.333333
## 78 NA NA
## 79 2.666667 1.666667
## 80 1.666667 3.000000
## 81 2.666667 4.000000
## 82 1.666667 1.666667
## 83 2.333333 1.000000
## 84 2.000000 2.000000
## 85 3.333333 3.000000
## 86 2.333333 4.000000
## 87 2.666667 3.666667
## 88 2.000000 2.666667
## PleasantScoreForNeutralMusic AngryScoreForAngryMusic
## 1 4.666667 4.333333
## 2 1.666667 4.000000
## 3 3.666667 2.666667
## 4 2.333333 2.333333
## 5 3.333333 2.000000
## 6 3.333333 4.000000
## 7 3.666667 3.333333
## 8 3.333333 1.000000
## 9 3.333333 3.000000
## 10 2.333333 3.000000
## 11 4.000000 4.333333
## 12 4.333333 4.000000
## 13 4.000000 2.666667
## 14 4.333333 4.333333
## 15 3.666667 4.333333
## 16 3.666667 3.000000
## 17 4.000000 3.333333
## 18 5.000000 4.000000
## 19 4.333333 4.000000
## 20 4.666667 2.666667
## 21 3.000000 2.666667
## 22 3.666667 3.000000
## 23 2.333333 4.333333
## 24 4.666667 1.000000
## 25 3.333333 4.000000
## 26 3.666667 4.666667
## 27 4.666667 4.666667
## 28 4.666667 4.666667
## 29 4.333333 2.333333
## 30 2.333333 2.666667
## 31 3.666667 4.333333
## 32 3.666667 4.666667
## 33 4.333333 1.333333
## 34 3.000000 3.333333
## 35 4.666667 3.666667
## 36 5.000000 4.333333
## 37 4.666667 2.666667
## 38 2.333333 3.666667
## 39 3.333333 3.000000
## 40 3.333333 4.666667
## 41 3.666667 3.000000
## 42 2.000000 2.666667
## 43 4.666667 3.666667
## 44 2.666667 4.666667
## 45 4.333333 3.666667
## 46 2.000000 3.666667
## 47 4.333333 3.666667
## 48 4.666667 3.666667
## 49 4.000000 4.000000
## 50 3.666667 2.333333
## 51 4.333333 3.666667
## 52 3.666667 2.666667
## 53 5.000000 4.000000
## 54 3.333333 4.333333
## 55 3.666667 2.333333
## 56 2.666667 4.666667
## 57 4.666667 3.333333
## 58 3.666667 4.333333
## 59 4.333333 5.000000
## 60 2.666667 4.333333
## 61 3.666667 3.666667
## 62 4.000000 3.666667
## 63 3.000000 4.333333
## 64 4.666667 4.333333
## 65 3.000000 1.333333
## 66 3.000000 4.333333
## 67 5.000000 4.000000
## 68 5.000000 4.000000
## 69 4.000000 4.000000
## 70 3.000000 4.000000
## 71 2.666667 2.666667
## 72 2.333333 1.666667
## 73 4.333333 4.333333
## 74 4.666667 1.666667
## 75 5.000000 4.333333
## 76 4.333333 3.000000
## 77 1.666667 4.000000
## 78 NA NA
## 79 4.666667 3.333333
## 80 4.333333 3.333333
## 81 1.666667 3.333333
## 82 4.666667 1.666667
## 83 3.666667 2.666667
## 84 4.333333 4.333333
## 85 2.666667 3.000000
## 86 5.000000 3.666667
## 87 4.333333 4.666667
## 88 4.333333 4.333333
## AngryScoreForExcitingMusic AngryScoreForNeutralMusic
## 1 3.333333 1.666667
## 2 2.333333 1.333333
## 3 1.000000 1.333333
## 4 1.666667 1.000000
## 5 1.333333 1.000000
## 6 1.666667 1.000000
## 7 1.666667 1.333333
## 8 1.000000 1.000000
## 9 1.333333 1.333333
## 10 1.333333 1.000000
## 11 1.666667 1.000000
## 12 3.000000 1.333333
## 13 1.000000 1.000000
## 14 2.000000 1.333333
## 15 1.666667 1.000000
## 16 1.000000 1.000000
## 17 1.000000 1.000000
## 18 1.666667 1.000000
## 19 1.666667 1.000000
## 20 1.000000 1.000000
## 21 1.000000 1.000000
## 22 1.666667 1.000000
## 23 2.000000 1.000000
## 24 1.000000 1.000000
## 25 3.666667 2.333333
## 26 3.000000 1.666667
## 27 2.000000 1.000000
## 28 2.333333 1.000000
## 29 1.333333 1.000000
## 30 3.333333 1.333333
## 31 1.666667 1.000000
## 32 3.333333 2.000000
## 33 1.666667 1.333333
## 34 1.666667 1.000000
## 35 2.666667 2.333333
## 36 2.000000 1.000000
## 37 1.000000 1.000000
## 38 2.666667 2.000000
## 39 3.000000 1.333333
## 40 3.333333 1.333333
## 41 1.000000 1.000000
## 42 3.333333 1.666667
## 43 3.333333 1.000000
## 44 4.000000 2.000000
## 45 1.000000 1.000000
## 46 4.666667 1.000000
## 47 4.000000 1.333333
## 48 1.666667 1.000000
## 49 2.333333 1.000000
## 50 1.000000 1.000000
## 51 2.666667 1.333333
## 52 1.000000 1.000000
## 53 2.666667 1.000000
## 54 1.666667 1.000000
## 55 2.000000 1.000000
## 56 1.000000 1.000000
## 57 2.333333 1.000000
## 58 1.666667 1.333333
## 59 2.666667 1.000000
## 60 1.333333 1.333333
## 61 1.000000 1.000000
## 62 1.666667 1.000000
## 63 2.000000 1.000000
## 64 3.666667 1.000000
## 65 1.666667 4.000000
## 66 2.333333 1.666667
## 67 1.000000 1.000000
## 68 1.666667 1.000000
## 69 2.333333 1.000000
## 70 1.333333 1.666667
## 71 1.000000 1.000000
## 72 1.000000 1.000000
## 73 1.333333 1.000000
## 74 1.666667 3.333333
## 75 1.000000 1.000000
## 76 1.000000 1.000000
## 77 4.000000 2.666667
## 78 NA NA
## 79 3.333333 2.333333
## 80 1.666667 1.333333
## 81 1.000000 1.000000
## 82 1.000000 1.000000
## 83 2.000000 2.000000
## 84 2.000000 1.000000
## 85 1.000000 2.333333
## 86 2.000000 1.000000
## 87 2.000000 1.000000
## 88 1.666667 1.000000
## ExcitedScoreForExcitingMusic ExcitedScoreForNeutralMusic
## 1 4.000000 2.000000
## 2 2.333333 1.666667
## 3 4.000000 1.666667
## 4 3.000000 2.000000
## 5 3.000000 1.333333
## 6 3.666667 1.000000
## 7 4.000000 1.666667
## 8 5.000000 1.666667
## 9 3.000000 1.666667
## 10 3.000000 1.333333
## 11 4.666667 1.333333
## 12 4.000000 2.000000
## 13 3.666667 2.000000
## 14 4.666667 3.000000
## 15 3.333333 1.000000
## 16 2.000000 2.000000
## 17 4.333333 1.333333
## 18 3.333333 1.000000
## 19 1.666667 1.000000
## 20 4.333333 1.000000
## 21 3.666667 1.000000
## 22 4.333333 1.333333
## 23 4.666667 1.000000
## 24 4.333333 1.000000
## 25 4.333333 1.666667
## 26 4.000000 1.000000
## 27 4.000000 1.666667
## 28 4.666667 2.000000
## 29 3.666667 2.666667
## 30 3.000000 1.666667
## 31 3.333333 1.333333
## 32 3.666667 2.000000
## 33 5.000000 1.333333
## 34 3.000000 1.000000
## 35 2.666667 2.000000
## 36 5.000000 2.000000
## 37 4.000000 1.000000
## 38 3.000000 2.000000
## 39 3.000000 1.333333
## 40 4.000000 1.666667
## 41 4.000000 1.666667
## 42 3.333333 2.000000
## 43 3.666667 2.333333
## 44 3.333333 2.000000
## 45 2.666667 1.000000
## 46 5.000000 2.333333
## 47 4.000000 1.333333
## 48 4.000000 1.666667
## 49 3.666667 1.333333
## 50 2.333333 1.000000
## 51 4.666667 2.333333
## 52 4.000000 1.333333
## 53 3.666667 2.000000
## 54 3.666667 3.000000
## 55 3.000000 1.000000
## 56 3.333333 1.666667
## 57 3.000000 1.000000
## 58 4.000000 2.333333
## 59 4.333333 2.000000
## 60 3.666667 1.666667
## 61 4.000000 1.333333
## 62 4.666667 1.333333
## 63 2.666667 1.666667
## 64 3.666667 1.333333
## 65 1.666667 3.333333
## 66 1.666667 3.666667
## 67 3.333333 1.000000
## 68 4.666667 1.000000
## 69 4.333333 1.000000
## 70 2.666667 1.000000
## 71 4.000000 1.666667
## 72 4.666667 1.666667
## 73 4.333333 1.333333
## 74 2.000000 4.000000
## 75 2.000000 1.333333
## 76 4.333333 1.333333
## 77 3.000000 3.000000
## 78 NA NA
## 79 4.333333 3.000000
## 80 4.000000 1.333333
## 81 4.000000 1.000000
## 82 2.000000 1.666667
## 83 2.333333 2.000000
## 84 4.000000 1.000000
## 85 3.666667 1.333333
## 86 5.000000 3.666667
## 87 4.000000 1.666667
## 88 4.333333 1.333333
## ActiveScoreForExcitingMusic ActiveScoreForNeutralMusic
## 1 4.666667 2.000000
## 2 2.000000 1.333333
## 3 5.000000 1.666667
## 4 3.000000 1.333333
## 5 3.333333 1.333333
## 6 3.333333 1.666667
## 7 4.666667 1.666667
## 8 3.333333 2.000000
## 9 4.000000 1.333333
## 10 3.000000 1.666667
## 11 3.666667 1.333333
## 12 4.666667 1.666667
## 13 3.666667 1.666667
## 14 4.666667 2.666667
## 15 3.666667 1.333333
## 16 2.333333 2.000000
## 17 5.000000 2.333333
## 18 3.666667 2.000000
## 19 3.333333 1.000000
## 20 5.000000 1.333333
## 21 3.666667 1.000000
## 22 4.666667 1.666667
## 23 4.666667 1.333333
## 24 4.666667 1.000000
## 25 3.666667 1.333333
## 26 3.666667 1.000000
## 27 4.333333 1.000000
## 28 4.666667 1.000000
## 29 4.666667 2.333333
## 30 3.000000 1.333333
## 31 5.000000 1.666667
## 32 4.333333 2.666667
## 33 4.666667 1.666667
## 34 3.666667 1.666667
## 35 4.000000 2.666667
## 36 5.000000 2.333333
## 37 4.000000 2.333333
## 38 2.333333 2.000000
## 39 4.666667 1.333333
## 40 4.666667 1.666667
## 41 4.333333 1.333333
## 42 1.666667 1.666667
## 43 4.333333 2.000000
## 44 2.000000 1.000000
## 45 4.000000 2.000000
## 46 5.000000 2.000000
## 47 5.000000 1.333333
## 48 4.666667 1.666667
## 49 4.333333 1.333333
## 50 4.000000 1.000000
## 51 4.333333 1.666667
## 52 5.000000 2.333333
## 53 5.000000 1.000000
## 54 3.333333 2.000000
## 55 3.333333 1.333333
## 56 4.333333 1.666667
## 57 4.000000 1.666667
## 58 3.666667 3.333333
## 59 5.000000 1.666667
## 60 4.333333 2.000000
## 61 4.333333 1.333333
## 62 5.000000 1.666667
## 63 4.666667 1.666667
## 64 3.666667 1.333333
## 65 1.666667 3.333333
## 66 4.000000 2.000000
## 67 4.333333 1.333333
## 68 5.000000 1.000000
## 69 4.333333 1.000000
## 70 4.000000 1.333333
## 71 5.000000 2.000000
## 72 5.000000 2.000000
## 73 4.000000 1.000000
## 74 2.666667 1.333333
## 75 1.666667 1.666667
## 76 4.666667 1.000000
## 77 4.000000 1.666667
## 78 NA NA
## 79 4.000000 2.000000
## 80 4.333333 1.666667
## 81 4.333333 1.666667
## 82 4.666667 1.333333
## 83 3.333333 2.000000
## 84 4.000000 1.333333
## 85 5.000000 1.000000
## 86 5.000000 1.666667
## 87 4.666667 1.333333
## 88 5.000000 1.000000
## ExcitedScoreForAngryMusic ActiveScoreForAngryMusic
## 1 3.333333 4.000000
## 2 2.666667 4.000000
## 3 2.666667 3.666667
## 4 4.333333 4.666667
## 5 3.333333 2.666667
## 6 3.333333 4.333333
## 7 3.333333 3.333333
## 8 5.000000 3.666667
## 9 4.333333 4.000000
## 10 3.333333 3.666667
## 11 4.000000 4.666667
## 12 4.333333 4.333333
## 13 3.666667 3.333333
## 14 2.333333 3.000000
## 15 4.000000 4.000000
## 16 3.333333 4.000000
## 17 4.666667 4.666667
## 18 5.000000 4.666667
## 19 4.666667 4.333333
## 20 2.000000 3.000000
## 21 3.000000 3.000000
## 22 4.000000 3.666667
## 23 4.000000 4.000000
## 24 4.000000 3.666667
## 25 4.000000 4.666667
## 26 4.666667 4.666667
## 27 4.666667 4.000000
## 28 4.333333 3.333333
## 29 3.333333 4.000000
## 30 2.666667 3.000000
## 31 2.666667 4.000000
## 32 4.666667 4.333333
## 33 4.000000 3.000000
## 34 3.333333 3.333333
## 35 2.666667 3.333333
## 36 4.000000 4.000000
## 37 2.000000 1.000000
## 38 4.000000 3.000000
## 39 4.666667 5.000000
## 40 5.000000 3.333333
## 41 4.000000 4.666667
## 42 4.000000 3.666667
## 43 3.666667 4.666667
## 44 4.333333 2.666667
## 45 1.666667 3.333333
## 46 4.666667 4.000000
## 47 4.666667 4.666667
## 48 3.333333 3.666667
## 49 4.666667 4.666667
## 50 2.333333 3.000000
## 51 4.666667 4.333333
## 52 4.000000 4.333333
## 53 5.000000 5.000000
## 54 1.333333 4.000000
## 55 1.666667 1.666667
## 56 3.666667 4.333333
## 57 4.333333 4.333333
## 58 3.666667 4.333333
## 59 5.000000 5.000000
## 60 3.333333 4.000000
## 61 1.666667 5.000000
## 62 4.000000 3.666667
## 63 4.333333 4.666667
## 64 4.333333 5.000000
## 65 1.000000 1.333333
## 66 2.000000 3.666667
## 67 4.333333 4.333333
## 68 3.666667 4.000000
## 69 1.333333 4.000000
## 70 4.000000 4.333333
## 71 4.000000 4.000000
## 72 3.666667 3.333333
## 73 4.333333 3.333333
## 74 2.000000 3.333333
## 75 3.666667 4.666667
## 76 3.666667 4.666667
## 77 4.333333 4.000000
## 78 NA NA
## 79 2.333333 4.000000
## 80 3.666667 3.666667
## 81 4.000000 3.000000
## 82 3.666667 3.000000
## 83 3.000000 3.333333
## 84 5.000000 4.333333
## 85 4.000000 4.666667
## 86 5.000000 5.000000
## 87 4.666667 4.000000
## 88 5.000000 4.333333It’s good practice to assign a new variable name (in this case
filtered_d) to a data frame when you change it in an
important way, or apply a code chunk that shouldn’t be run twice. This
helps prevent you seeing different results when you run your code in
chunks (and might run one multiple times, or skip it, etc.) vs. knit the
document.
get rid of unnecessary columns
The dataset contains a bunch of columns we don’t care about:
- The dataset contains three subject columns, which are identical except for a single NA which is not mentioned in the protocol, and so is likely an error.
- Columns telling us the path to the executable run for each part of the experiment, we don’t really care about that.
- Etc.
To get rid of these, we’ll use the select function to
take only the columns we need.
filtered_d = filtered_d %>%
select(c("Subject", "Cond"), # Generally important columns for both hypotheses
contains("Game"), # we want all the game columns for hypothesis 1
-contains("Intro"), -c("WhichGames", "GameComments"), # except these
starts_with("DinerDashWith"), c("SOFMusicEnemies", "SOFNoMusicEnemies")) # These columns are for hypothesis 2Even better, let’s split this into separate data frames for
hypothesis 1 and hypothesis 2, since they are different types of
experiments with different measurements, and therefore different
analyses that will need to be performed. Now that we’ve cleaned up the
data, this is pretty easy to do! We’ll just drop the columns that are
for the other hypothesis. The select function lets us
choose which columns to remove (instead of which to keep) by putting a
minus sign in front of them. First, let’s create a dataset for the
rating hypothesis by getting rid of the game performance columns:
rating_hyp_d = filtered_d %>%
filter(is.na(DoNotUseVideoGamePerformanceData)) %>% # first, let's get rid of the subjects who did so poorly on one game that their data is unusable
select(-DoNotUseVideoGamePerformanceData, # now get rid of that column
-starts_with("DinerDash"), # and the other columns we don't need
-starts_with("SOF"))
show(rating_hyp_d)## Subject Cond Game1Angry1 Game1Angry2 Game1Angry3 Game1AngryFriends
## 1 1 2 6 6 5 2
## 2 3 1 6 5 7 2
## 3 6 6 5 5 6 3
## 4 9 5 4 1 4 7
## 5 10 1 7 5 7 6
## 6 11 2 3 4 3 3
## 7 12 4 5 6 1 7
## 8 16 3 4 5 5 4
## 9 18 1 7 7 5 5
## 10 20 3 5 3 7 6
## 11 21 6 4 1 4 1
## 12 22 5 4 2 2 7
## 13 24 2 5 5 4 3
## 14 25 2 4 7 6 4
## 15 26 1 6 2 6 1
## 16 35 2 2 2 3 5
## 17 36 6 6 5 5 6
## 18 38 6 1 5 4 1
## 19 41 5 6 4 6 3
## 20 42 2 6 6 7 5
## 21 43 6 5 6 7 5
## 22 44 2 5 6 5 3
## 23 45 3 5 5 6 5
## 24 47 4 4 2 5 4
## 25 49 5 5 6 5 4
## 26 52 1 5 3 4 2
## 27 53 6 7 6 6 2
## 28 54 2 3 6 7 6
## 29 57 2 3 3 4 1
## 30 58 5 5 1 7 2
## 31 59 1 7 7 7 5
## 32 60 6 6 7 5 6
## 33 67 4 1 1 1 1
## 34 68 3 6 7 6 4
## 35 69 6 7 7 7 6
## 36 70 2 5 5 7 6
## 37 71 5 6 6 1 6
## 38 73 1 3 1 4 2
## 39 74 2 4 5 7 2
## 40 81 5 5 5 7 6
## 41 82 3 6 6 5 5
## 42 83 4 7 6 4 1
## 43 84 4 7 7 7 4
## 44 85 5 2 5 4 1
## 45 86 3 4 3 6 2
## 46 88 6 7 7 5 4
## 47 90 3 5 5 5 7
## Game1AngryStrangers Game1CalmFriends Game1CalmStrangers Game1ExcitedFriends
## 1 5 2 2 1
## 2 2 2 2 2
## 3 4 5 4 6
## 4 7 4 5 3
## 5 6 2 2 5
## 6 5 1 2 2
## 7 7 3 3 4
## 8 7 2 1 1
## 9 6 2 3 3
## 10 7 2 2 4
## 11 1 1 1 2
## 12 7 2 2 2
## 13 5 1 1 1
## 14 5 2 2 5
## 15 1 7 7 5
## 16 6 4 4 2
## 17 5 2 2 4
## 18 1 6 5 4
## 19 7 1 2 4
## 20 7 2 2 6
## 21 7 1 1 2
## 22 4 5 3 5
## 23 5 3 3 4
## 24 4 4 4 4
## 25 5 4 4 5
## 26 3 5 4 5
## 27 4 4 3 6
## 28 6 3 3 4
## 29 4 1 1 1
## 30 1 4 4 3
## 31 7 2 2 4
## 32 7 1 2 5
## 33 1 3 3 4
## 34 7 1 4 3
## 35 4 3 2 5
## 36 6 1 1 1
## 37 4 3 1 5
## 38 7 2 2 2
## 39 7 4 2 7
## 40 5 4 5 5
## 41 6 3 1 5
## 42 6 2 1 7
## 43 7 1 1 1
## 44 1 1 1 1
## 45 3 2 2 5
## 46 1 4 4 7
## 47 7 1 1 4
## Game1ExcitedStrangers Game1Exciting1 Game1Exciting2 Game1Exciting3
## 1 2 3 2 6
## 2 2 2 3 4
## 3 4 3 2 4
## 4 2 3 4 2
## 5 5 6 3 4
## 6 3 1 5 1
## 7 5 4 4 5
## 8 3 3 1 3
## 9 3 5 5 3
## 10 4 2 1 2
## 11 2 5 5 4
## 12 4 2 1 2
## 13 2 4 1 4
## 14 6 2 4 6
## 15 5 7 4 7
## 16 1 1 5 1
## 17 4 3 2 2
## 18 4 1 4 2
## 19 6 1 3 3
## 20 4 4 3 5
## 21 2 3 2 3
## 22 5 3 4 3
## 23 4 5 2 6
## 24 4 1 1 1
## 25 5 4 3 4
## 26 5 4 2 2
## 27 5 6 2 7
## 28 4 1 1 1
## 29 2 2 2 2
## 30 6 1 1 1
## 31 4 4 3 2
## 32 4 3 3 4
## 33 3 1 4 3
## 34 5 3 3 4
## 35 3 5 5 2
## 36 1 1 1 1
## 37 6 3 5 1
## 38 2 5 5 3
## 39 4 1 1 1
## 40 3 1 2 3
## 41 4 2 1 4
## 42 7 6 1 1
## 43 3 3 1 5
## 44 1 1 1 3
## 45 5 3 4 2
## 46 4 7 7 6
## 47 1 1 1 1
## Game1Neutral1 Game1Neutral2 Game1Neutral3 Game2Angry1 Game2Angry2
## 1 2 4 4 6 4
## 2 1 2 3 5 3
## 3 2 2 4 6 5
## 4 2 1 1 1 1
## 5 1 2 1 6 5
## 6 1 1 2 6 5
## 7 1 1 1 7 7
## 8 1 1 2 1 4
## 9 2 3 1 7 7
## 10 1 1 1 4 4
## 11 1 1 2 4 2
## 12 1 1 1 4 5
## 13 1 1 1 4 4
## 14 1 2 2 1 6
## 15 1 4 3 7 4
## 16 2 3 5 4 5
## 17 2 2 1 5 4
## 18 3 6 3 1 1
## 19 2 3 4 6 6
## 20 2 3 1 6 6
## 21 1 1 1 3 2
## 22 3 2 2 5 5
## 23 3 4 2 6 5
## 24 1 7 7 3 2
## 25 3 3 3 7 6
## 26 2 3 3 5 2
## 27 3 1 1 6 6
## 28 1 1 1 5 6
## 29 2 2 2 4 4
## 30 1 1 1 6 5
## 31 2 5 3 7 7
## 32 3 2 1 5 5
## 33 3 4 1 4 1
## 34 2 2 2 5 5
## 35 1 3 2 5 7
## 36 1 1 1 5 7
## 37 1 1 1 4 6
## 38 3 3 2 4 3
## 39 1 1 1 4 7
## 40 1 3 4 3 4
## 41 1 1 1 4 5
## 42 1 1 1 7 7
## 43 1 1 2 7 7
## 44 2 1 2 1 1
## 45 3 3 2 4 4
## 46 2 1 1 7 7
## 47 1 1 6 5 1
## Game2Angry3 Game2AngryFriends Game2AngryStrangers Game2CalmFriends
## 1 6 3 6 1
## 2 6 3 3 3
## 3 6 3 5 3
## 4 2 1 7 7
## 5 6 6 7 1
## 6 4 5 6 2
## 7 4 6 7 1
## 8 6 3 6 1
## 9 6 4 6 2
## 10 7 6 7 2
## 11 4 1 2 1
## 12 5 7 7 2
## 13 3 2 5 1
## 14 5 7 6 2
## 15 5 1 1 7
## 16 4 4 4 2
## 17 4 4 5 1
## 18 7 1 1 6
## 19 5 4 6 2
## 20 6 5 7 4
## 21 7 5 7 2
## 22 5 6 4 5
## 23 4 6 5 3
## 24 5 4 4 4
## 25 4 5 5 4
## 26 5 3 3 4
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## Game2CalmStrangers Game2ExcitedFriends Game2ExcitedStrangers Game2Exciting1
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## Game3ExcitedStrangers Game3Exciting1 Game3Exciting2 Game3Exciting3
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## Game3Neutral1 Game3Neutral2 Game3Neutral3 Game4Angry1 Game4Angry2
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## 47 4 5 1 2 5show(rating_hyp_d)## Subject Cond Game1Angry1 Game1Angry2 Game1Angry3 Game1AngryFriends
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## Game1AngryStrangers Game1CalmFriends Game1CalmStrangers Game1ExcitedFriends
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## 46 3 2 1 1
## 47 7 2 1 1
## Game3Neutral1 Game3Neutral2 Game3Neutral3 Game4Angry1 Game4Angry2
## 1 5 6 5 2 2
## 2 2 3 3 5 2
## 3 5 4 4 2 3
## 4 1 3 1 7 7
## 5 2 2 1 3 5
## 6 2 1 4 1 5
## 7 2 2 1 1 2
## 8 1 2 6 1 2
## 9 3 2 6 6 5
## 10 3 4 4 4 3
## 11 1 1 4 1 1
## 12 2 1 1 2 4
## 13 2 2 4 1 1
## 14 6 6 7 1 2
## 15 6 5 6 3 1
## 16 3 1 4 5 2
## 17 3 5 5 4 4
## 18 4 4 6 1 1
## 19 4 3 6 5 4
## 20 2 2 5 3 2
## 21 4 5 1 1 1
## 22 3 1 3 4 5
## 23 5 5 6 4 4
## 24 2 6 6 6 2
## 25 3 2 5 2 3
## 26 4 6 5 2 1
## 27 6 5 3 3 1
## 28 5 6 5 2 1
## 29 4 3 5 2 2
## 30 1 1 2 4 2
## 31 3 5 5 3 3
## 32 2 1 4 2 5
## 33 2 4 4 1 1
## 34 2 2 4 4 5
## 35 1 7 4 3 3
## 36 4 5 3 1 1
## 37 6 6 3 1 1
## 38 2 2 2 5 5
## 39 1 2 3 3 2
## 40 1 2 5 2 1
## 41 2 1 1 2 2
## 42 4 1 1 4 1
## 43 3 1 7 2 1
## 44 1 1 2 1 3
## 45 3 1 1 3 3
## 46 4 6 2 2 1
## 47 4 4 7 1 3
## Game4Angry3 Game4AngryFriends Game4AngryStrangers Game4CalmFriends
## 1 2 2 2 5
## 2 2 4 5 2
## 3 3 1 2 4
## 4 1 2 1 1
## 5 5 2 2 1
## 6 1 1 4 3
## 7 1 1 2 4
## 8 3 2 5 5
## 9 3 3 3 4
## 10 3 1 1 5
## 11 2 1 1 4
## 12 1 1 1 7
## 13 2 1 1 3
## 14 3 4 5 3
## 15 3 1 1 7
## 16 4 2 1 2
## 17 2 2 2 5
## 18 2 1 1 4
## 19 4 4 2 6
## 20 2 2 1 3
## 21 4 1 1 5
## 22 6 3 4 4
## 23 3 5 5 4
## 24 3 4 4 4
## 25 3 3 2 4
## 26 2 2 2 5
## 27 2 2 2 5
## 28 3 1 1 3
## 29 5 1 2 4
## 30 6 1 1 1
## 31 3 1 2 3
## 32 2 1 1 5
## 33 5 1 1 6
## 34 4 4 4 4
## 35 5 3 1 6
## 36 1 1 1 1
## 37 1 3 1 6
## 38 6 1 1 1
## 39 5 1 1 4
## 40 5 4 4 6
## 41 1 2 1 4
## 42 3 1 1 6
## 43 1 1 1 1
## 44 3 2 2 3
## 45 2 2 3 5
## 46 7 3 4 2
## 47 1 3 3 5
## Game4CalmStrangers Game4ExcitedFriends Game4ExcitedStrangers Game4Exciting1
## 1 5 7 4 5
## 2 4 4 5 7
## 3 4 5 4 2
## 4 1 4 1 4
## 5 1 6 3 5
## 6 4 3 6 1
## 7 6 7 7 3
## 8 4 7 4 2
## 9 3 7 5 2
## 10 4 3 6 2
## 11 5 5 4 4
## 12 4 7 7 6
## 13 4 5 4 1
## 14 2 5 2 1
## 15 6 3 2 3
## 16 2 7 2 3
## 17 5 6 5 4
## 18 5 3 5 1
## 19 5 7 5 2
## 20 5 7 6 4
## 21 4 7 5 6
## 22 5 4 5 1
## 23 4 4 3 6
## 24 4 4 4 3
## 25 4 5 5 4
## 26 4 5 5 5
## 27 4 7 7 4
## 28 2 6 7 3
## 29 3 6 3 3
## 30 1 7 6 3
## 31 1 7 6 5
## 32 4 6 5 3
## 33 3 6 3 1
## 34 4 7 5 4
## 35 2 6 6 4
## 36 1 7 7 7
## 37 5 3 4 1
## 38 1 7 7 6
## 39 4 7 7 5
## 40 5 7 7 1
## 41 3 5 4 5
## 42 5 7 7 3
## 43 1 7 7 7
## 44 2 4 4 1
## 45 3 5 4 3
## 46 6 7 7 4
## 47 4 7 7 2
## Game4Exciting2 Game4Exciting3 Game4Neutral1 Game4Neutral2 Game4Neutral3
## 1 5 2 1 5 2
## 2 4 5 3 2 4
## 3 4 3 3 5 5
## 4 7 3 6 2 2
## 5 6 4 2 4 2
## 6 4 5 1 5 2
## 7 4 6 4 5 1
## 8 2 4 2 3 4
## 9 2 2 1 2 1
## 10 4 5 4 5 3
## 11 3 2 2 1 2
## 12 3 1 5 1 2
## 13 3 2 5 3 5
## 14 5 4 7 7 5
## 15 5 5 6 6 7
## 16 7 6 4 5 3
## 17 5 5 4 3 3
## 18 2 1 6 5 4
## 19 2 5 3 2 6
## 20 6 6 4 1 1
## 21 3 3 5 2 2
## 22 4 2 2 5 4
## 23 5 6 5 3 2
## 24 1 3 1 5 4
## 25 4 6 5 3 3
## 26 6 5 4 5 4
## 27 7 5 6 1 1
## 28 6 7 6 3 2
## 29 6 3 5 5 4
## 30 3 3 5 1 1
## 31 5 5 4 4 4
## 32 7 5 6 4 1
## 33 2 1 2 3 4
## 34 4 5 3 2 2
## 35 2 4 6 3 1
## 36 7 6 4 4 4
## 37 1 1 5 6 5
## 38 7 5 2 2 2
## 39 2 4 4 2 1
## 40 4 6 7 5 3
## 41 7 5 6 6 4
## 42 6 7 1 1 1
## 43 7 7 3 3 2
## 44 4 1 1 1 4
## 45 5 5 3 4 1
## 46 1 2 5 3 1
## 47 4 5 1 2 5Now you try! Fill in the selection criteria to get rid of the “Game”
columns, which we don’t need for the performance hypothesis. (It’s
simpler than the code block above, because you don’t need to do a
filter first, only a select.)
performance_hyp_d = filtered_d %>%
select(-contains('Game')) # your code here: remove the columns containing "Game" in the name
show(performance_hyp_d)## Subject Cond DinerDashWithMusicScore DinerDashWithoutMusicScore
## 1 1 2 5830 5000
## 2 3 1 5370 1250
## 3 4 4 6921 6742
## 4 5 5 6750 5060
## 5 6 6 6380 5840
## 6 7 3 5170 5020
## 7 8 6 5690 5000
## 8 9 5 6440 6460
## 9 10 1 5480 2990
## 10 11 2 6210 5090
## 11 12 4 6270 5490
## 12 13 4 6150 5140
## 13 14 6 7440 NA
## 14 15 2 5660 5000
## 15 16 3 6810 5200
## 16 17 5 5950 3040
## 17 18 1 6160 5140
## 18 19 4 6240 5370
## 19 20 3 6650 5170
## 20 21 6 6500 3000
## 21 22 5 5770 5000
## 22 24 2 5950 5060
## 23 25 2 5550 5000
## 24 26 1 6560 5020
## 25 27 3 6190 5370
## 26 28 4 5930 5000
## 27 29 6 5990 5000
## 28 30 5 6160 5960
## 29 31 4 5020 970
## 30 32 5 5000 1090
## 31 33 3 5970 5000
## 32 34 1 6440 5000
## 33 35 2 6010 5000
## 34 36 6 5730 5060
## 35 37 1 5240 5060
## 36 38 6 7430 5840
## 37 39 4 5740 5000
## 38 40 3 5840 3340
## 39 41 5 5790 4189
## 40 42 2 6410 5090
## 41 43 6 7310 5000
## 42 44 2 6460 5170
## 43 45 3 6820 5060
## 44 46 1 5000 5000
## 45 47 4 5100 5000
## 46 48 5 6100 5000
## 47 49 5 5920 5370
## 48 50 3 6170 5680
## 49 51 4 5000 5000
## 50 52 1 5990 5000
## 51 53 6 5670 5530
## 52 54 2 5000 3140
## 53 55 4 5170 5000
## 54 56 3 5990 5000
## 55 57 2 5620 2870
## 56 58 5 6080 5150
## 57 59 1 5830 5000
## 58 60 6 6200 5490
## 59 61 3 6790 5000
## 60 62 6 6130 5210
## 61 63 1 5060 2200
## 62 64 2 6500 5170
## 63 65 4 3460 5000
## 64 66 5 6000 5670
## 65 67 4 5170 1210
## 66 68 3 5650 2960
## 67 69 6 5600 5170
## 68 70 2 5900 5860
## 69 71 5 5660 5000
## 70 72 1 7440 5020
## 71 73 1 6480 6180
## 72 74 2 5430 3160
## 73 75 6 6160 5430
## 74 76 5 5350 5500
## 75 77 4 5060 2180
## 76 78 3 5260 5000
## 77 79 6 5970 5140
## 78 80 2 NA NA
## 79 81 5 5670 5070
## 80 82 3 5960 5060
## 81 83 4 5630 5060
## 82 84 4 3290 2870
## 83 85 5 6150 6000
## 84 86 3 5940 5000
## 85 87 1 5170 5000
## 86 88 6 5866 5000
## 87 89 2 5820 3280
## 88 90 3 5000 3040
## SOFMusicEnemies SOFNoMusicEnemies
## 1 19 22
## 2 23 15
## 3 19 3
## 4 23 18
## 5 24 23
## 6 20 7
## 7 1 17
## 8 16 18
## 9 24 16
## 10 26 19
## 11 23 23
## 12 23 2
## 13 25 29
## 14 10 0
## 15 26 24
## 16 15 0
## 17 23 19
## 18 21 15
## 19 23 21
## 20 14 10
## 21 23 21
## 22 15 16
## 23 27 25
## 24 24 24
## 25 26 1
## 26 1 3
## 27 19 10
## 28 26 20
## 29 14 2
## 30 12 12
## 31 19 15
## 32 NA 25
## 33 23 25
## 34 24 18
## 35 7 15
## 36 26 24
## 37 0 0
## 38 14 20
## 39 25 15
## 40 23 19
## 41 30 27
## 42 22 24
## 43 23 13
## 44 1 1
## 45 28 27
## 46 25 2
## 47 24 17
## 48 0 17
## 49 NA 8
## 50 23 23
## 51 24 25
## 52 23 24
## 53 4 11
## 54 17 9
## 55 24 24
## 56 26 22
## 57 23 23
## 58 26 18
## 59 18 21
## 60 23 21
## 61 0 1
## 62 13 20
## 63 NA 13
## 64 23 8
## 65 27 19
## 66 19 21
## 67 25 24
## 68 28 16
## 69 26 19
## 70 23 16
## 71 36 27
## 72 24 24
## 73 11 15
## 74 25 6
## 75 25 15
## 76 17 2
## 77 20 17
## 78 NA NA
## 79 27 21
## 80 28 20
## 81 26 17
## 82 19 7
## 83 30 25
## 84 18 19
## 85 25 15
## 86 27 24
## 87 31 7
## 88 26 22Converting to long form
Now we want to convert the data to long form, to make the rest of our
manipulations easier. To do this, we can use pivot_longer
on the target columns. This will take many columns, and change the
column names into entries in a “key” column, while the values that were
in the original column will be turned into entries in a “value” column.
It’s easiest to see with an example:
tiny_demo_d = head(performance_hyp_d, 2) # get just the first two subjects performance data, for a demoFirst, take a look at the original wide-form data:
tiny_demo_d## Subject Cond DinerDashWithMusicScore DinerDashWithoutMusicScore
## 1 1 2 5830 5000
## 2 3 1 5370 1250
## SOFMusicEnemies SOFNoMusicEnemies
## 1 19 22
## 2 23 15Now, take a look at the long-form version:
tiny_demo_d %>% pivot_longer(cols=-c("Subject", "Cond"), # this tells it to transform all columns *except* these ones
names_to='Measurement',
values_to='Value')## # A tibble: 8 × 4
## Subject Cond Measurement Value
## <dbl> <dbl> <chr> <dbl>
## 1 1 2 DinerDashWithMusicScore 5830
## 2 1 2 DinerDashWithoutMusicScore 5000
## 3 1 2 SOFMusicEnemies 19
## 4 1 2 SOFNoMusicEnemies 22
## 5 3 1 DinerDashWithMusicScore 5370
## 6 3 1 DinerDashWithoutMusicScore 1250
## 7 3 1 SOFMusicEnemies 23
## 8 3 1 SOFNoMusicEnemies 15See how the columns have been converted into rows (except for the two we excluded), and the dataset has gone from wide to long?
Now let’s actually convert the performance dataset
performance_hyp_long_d = performance_hyp_d %>%
pivot_longer(cols=-c("Subject", "Cond"),
names_to='Measurement',
values_to='Score')
head(performance_hyp_long_d)## # A tibble: 6 × 4
## Subject Cond Measurement Score
## <dbl> <dbl> <chr> <dbl>
## 1 1 2 DinerDashWithMusicScore 5830
## 2 1 2 DinerDashWithoutMusicScore 5000
## 3 1 2 SOFMusicEnemies 19
## 4 1 2 SOFNoMusicEnemies 22
## 5 3 1 DinerDashWithMusicScore 5370
## 6 3 1 DinerDashWithoutMusicScore 1250And you can convert the rating dataset! (Call the “Key” column “Measurement” and call the “Value” column “Rating”, so that the code below will work)
show(rating_hyp_d$Key)## NULLrating_hyp_long_d = rating_hyp_d %>%
pivot_longer(cols=-c("Subject", "Cond"),
names_to='Measurement',
values_to='Rating')
show(rating_hyp_long_d)## # A tibble: 2,820 × 4
## Subject Cond Measurement Rating
## <dbl> <dbl> <chr> <dbl>
## 1 1 2 Game1Angry1 6
## 2 1 2 Game1Angry2 6
## 3 1 2 Game1Angry3 5
## 4 1 2 Game1AngryFriends 2
## 5 1 2 Game1AngryStrangers 5
## 6 1 2 Game1CalmFriends 2
## 7 1 2 Game1CalmStrangers 2
## 8 1 2 Game1ExcitedFriends 1
## 9 1 2 Game1ExcitedStrangers 2
## 10 1 2 Game1Exciting1 3
## # … with 2,810 more rowsSplitting columns
The measurement column in each dataset now contains a bunch of
different types of information. Really, we would like these to be
separate columns. For example, we could have one column telling you
which video-game it is, and one telling you whether there was music.
Tidyverse contains some handy features for splitting columns, but
unfortunately the measurement names here are not well suited to it (if
the different types of information were always the same length, or were
separated by a symbol like “.” or “_“, it would be easy). Thus we’ll
have to do a bit of manual testing. We can use the mutate
function in dplyr to create new columns as functions of old ones (or
alter existing columns). We’ll also use the grepl function,
which lets us test whether a regular expression (a fancy type
of search pattern) is contained in a column name. For most your
purposes, you can probably just use grepl to search for strings, but
there are some other quite useful functions in regular expressions, like
the”or”” function (|) we use below.
performance_hyp_long_d = performance_hyp_long_d %>%
mutate(ConfrontationalGame = grepl("SOF", Measurement), # create a new variable that will say whether the measurement was of the game soldier of fortune (SOF).
WithMusic = !grepl("NoMusic|WithoutMusic", Measurement), # creates a new column named WithMusic, which is False if the measurement contains *either* "NoMusic" or "WithoutMusic"
MusicCondition = factor(ifelse(Cond > 3, Cond-3, Cond), levels = 1:3, labels = c("Anger", "Exciting", "Neutral"))) # Get rid of uninterpretable condition labelsshow(rating_hyp_long_d)## # A tibble: 2,820 × 4
## Subject Cond Measurement Rating
## <dbl> <dbl> <chr> <dbl>
## 1 1 2 Game1Angry1 6
## 2 1 2 Game1Angry2 6
## 3 1 2 Game1Angry3 5
## 4 1 2 Game1AngryFriends 2
## 5 1 2 Game1AngryStrangers 5
## 6 1 2 Game1CalmFriends 2
## 7 1 2 Game1CalmStrangers 2
## 8 1 2 Game1ExcitedFriends 1
## 9 1 2 Game1ExcitedStrangers 2
## 10 1 2 Game1Exciting1 3
## # … with 2,810 more rowsNow you can help! For the rating dataset, write a test on a
measurement name, using grepl or %in% to
figure out whether it’s a recall or a music rating. Your new
IsRecall column should be true if the measurement name
contain either “Friends” or “Strangers”.
rating_hyp_long_d = rating_hyp_long_d %>%
mutate(
IsRecall = grepl("Friends|Strangers", Measurement)
)show(rating_hyp_long_d)## # A tibble: 2,820 × 5
## Subject Cond Measurement Rating IsRecall
## <dbl> <dbl> <chr> <dbl> <lgl>
## 1 1 2 Game1Angry1 6 FALSE
## 2 1 2 Game1Angry2 6 FALSE
## 3 1 2 Game1Angry3 5 FALSE
## 4 1 2 Game1AngryFriends 2 TRUE
## 5 1 2 Game1AngryStrangers 5 TRUE
## 6 1 2 Game1CalmFriends 2 TRUE
## 7 1 2 Game1CalmStrangers 2 TRUE
## 8 1 2 Game1ExcitedFriends 1 TRUE
## 9 1 2 Game1ExcitedStrangers 2 TRUE
## 10 1 2 Game1Exciting1 3 FALSE
## # … with 2,810 more rowsHere are a couple other useful ways of manipulating columns. (You won’t remember all the functions you see here now, but that’s okay. You can always reference this tutorial later if there’s something you need to figure out how to do.)
rating_hyp_long_d = rating_hyp_long_d %>%
mutate(
GameNumber = as.numeric(substr(rating_hyp_long_d$Measurement, 5, 5)),
ConfrontationalGame = GameNumber <= 2, # in a mutate, we can use a column we created (or changed) right away. Games 1 and 2 are confrontational, games 3 and 4 are not.
Emotion = str_extract(Measurement, "Angry|Neutral|Excited|Exciting|Calm"),
Emotion = ifelse(Emotion == "Excited", "Exciting", # this just gets rid of some annoying labeling choices
ifelse(Emotion == "Calm", "Neutral", Emotion))
) Groups, Summaries, and Results
Performance Hypothesis
For the performance data, we need to do a little bit of manipulation of the columns in order to get to the performance measures the experimenters actually used. Because they want to compare changes in performance across games that have very different scoring systems, the easiest solution is to compare z-scores. The way they did this was to z-score performance before music, z-score performance after music, and then create a difference measure which is a difference of z-scores. (To my mind, this is actually not quite the correct way to analyze this data, but like the replication we will follow the original authors.)
We’ll add a new z-scored value column. However, we have to be
careful! We want to z-score within groups of the rows, that are
all the same type of measurement. For example, we want to z-score the
“DinnerDashWithMusic” scores with respect to eachother, but
not with respect to the scores from the other game, for
example. We can use the group_by function to set groups,
and then all the changes we apply will only occur within those groups
until we ungroup the dataset.
To make this more concrete, let’s see how the group_by
function can let us compute means within different groups, for example
mean scores on the two different games.
performance_hyp_long_d %>%
group_by(ConfrontationalGame) %>%
summarize(AvgScore = mean(Score, na.rm=T)) # the na.rm tells R to ignore NA values## # A tibble: 2 × 2
## ConfrontationalGame AvgScore
## <lgl> <dbl>
## 1 FALSE 5288.
## 2 TRUE 18.3This makes it clear why we can’t just z-score the games together! The
scores are very different between games. So let’s z-score within groups
(using the scale function):
performance_hyp_long_d = performance_hyp_long_d %>%
group_by(ConfrontationalGame, WithMusic) %>% # we're going to compute four sets of z-scores, one for the confrontational game without music, one for the confrontational game with, one for the nonconfrontational game without music, and one for the nonconfrontational game with
mutate(z_scored_performance = scale(Score)) %>%
ungroup()Rating Hypothesis
The rating hypothesis analysis also requires some grouped
manipulation. The experimenters collected repeated measures on ratings
in each emotion category and each music/recall category from each game.
For this analysis, they averaged all the ratings over the following two
variables: the given emotion and the game type, to produce a nice
summary. Your job is to implement this, calling the new variable
MeanRating, and save the summarized data in a new data frame called
rating_summary_d. (Hint: use a group_by and a
summarize.)
show(rating_hyp_long_d)## # A tibble: 2,820 × 8
## Subject Cond Measurement Rating IsRecall GameNum…¹ Confr…² Emotion
## <dbl> <dbl> <chr> <dbl> <lgl> <dbl> <lgl> <chr>
## 1 1 2 Game1Angry1 6 FALSE 1 TRUE Angry
## 2 1 2 Game1Angry2 6 FALSE 1 TRUE Angry
## 3 1 2 Game1Angry3 5 FALSE 1 TRUE Angry
## 4 1 2 Game1AngryFriends 2 TRUE 1 TRUE Angry
## 5 1 2 Game1AngryStrangers 5 TRUE 1 TRUE Angry
## 6 1 2 Game1CalmFriends 2 TRUE 1 TRUE Neutral
## 7 1 2 Game1CalmStrangers 2 TRUE 1 TRUE Neutral
## 8 1 2 Game1ExcitedFriends 1 TRUE 1 TRUE Exciti…
## 9 1 2 Game1ExcitedStrangers 2 TRUE 1 TRUE Exciti…
## 10 1 2 Game1Exciting1 3 FALSE 1 TRUE Exciti…
## # … with 2,810 more rows, and abbreviated variable names ¹GameNumber,
## # ²ConfrontationalGamerating_summary_d = rating_hyp_long_d %>%
group_by(Emotion, ConfrontationalGame) %>%
summarize(MeanRating = mean(Rating, na.rm=T))## `summarise()` has grouped output by 'Emotion'. You can override using the
## `.groups` argument.show(rating_summary_d)## # A tibble: 6 × 3
## # Groups: Emotion [3]
## Emotion ConfrontationalGame MeanRating
## <chr> <lgl> <dbl>
## 1 Angry FALSE 2.72
## 2 Angry TRUE 4.68
## 3 Exciting FALSE 3.97
## 4 Exciting TRUE 3.05
## 5 Neutral FALSE 3.68
## 6 Neutral TRUE 2.16Let’s take a look at the result:
rating_summary_d## # A tibble: 6 × 3
## # Groups: Emotion [3]
## Emotion ConfrontationalGame MeanRating
## <chr> <lgl> <dbl>
## 1 Angry FALSE 2.72
## 2 Angry TRUE 4.68
## 3 Exciting FALSE 3.97
## 4 Exciting TRUE 3.05
## 5 Neutral FALSE 3.68
## 6 Neutral TRUE 2.16And a simple bar plot (don’t worry too much about what exactly this code is doing):
ggplot(rating_summary_d, aes(x=ConfrontationalGame, y=MeanRating, fill=Emotion)) +
geom_bar(position="dodge", stat="identity") +
scale_fill_brewer(palette="Set1")
Up to reordering (and the fact that we didn’t compute error bars), this is a pretty decent replication of Fig. 1 from the original Tamir et al. paper. The ratings were highest for Angry in the confrontational game, and lowest for Angry in the non-confrontational game.
And the long form dataset makes it easy to run a linear model (don’t worry too much about this, we’ll talk more about it in 252).
model = lm(Rating ~ ConfrontationalGame * Emotion, rating_hyp_long_d)
summary(model)##
## Call:
## lm(formula = Rating ~ ConfrontationalGame * Emotion, data = rating_hyp_long_d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.6787 -1.1553 -0.0468 1.3170 4.8447
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.71702 0.07965 34.114 <2e-16
## ConfrontationalGameTRUE 1.96170 0.11264 17.416 <2e-16
## EmotionExciting 1.25319 0.11264 11.126 <2e-16
## EmotionNeutral 0.96596 0.11264 8.576 <2e-16
## ConfrontationalGameTRUE:EmotionExciting -2.88511 0.15929 -18.112 <2e-16
## ConfrontationalGameTRUE:EmotionNeutral -3.48936 0.15929 -21.905 <2e-16
##
## (Intercept) ***
## ConfrontationalGameTRUE ***
## EmotionExciting ***
## EmotionNeutral ***
## ConfrontationalGameTRUE:EmotionExciting ***
## ConfrontationalGameTRUE:EmotionNeutral ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.727 on 2814 degrees of freedom
## Multiple R-squared: 0.1896, Adjusted R-squared: 0.1882
## F-statistic: 131.7 on 5 and 2814 DF, p-value: < 2.2e-16Performance Hypothesis (Continued)
There are still a few more steps to go for the performance hypothesis. We need to take a difference score to see how people improved from before hearing the music to after, and then see if the improvement is larger if they heard music congruent with the type of game.
To compute the difference score, we have to make our data a bit
wider. We now want to subtract the pre-music scores from the post-music
scores, which is easiest to do if they are in two different columns. To
do this we’ll use the pivot_wider function (which is more
or less the opposite of pivot_longer)
performance_diff_d = performance_hyp_long_d %>%
mutate(WithMusic = factor(WithMusic, levels=c(F, T), labels=c("PreMusic", "PostMusic"))) %>% # first, tweak the variable so our code is easier to read.
select(-c("Score", "Measurement")) %>% # now we remove columns we don't need (bonus: leave them in and see if you can understand what goes wrong!)
pivot_wider(names_from=WithMusic,
values_from=z_scored_performance) %>%
mutate(ImprovementScore=PostMusic-PreMusic)Let’s take a look at the end result:
performance_diff_d## # A tibble: 176 × 7
## Subject Cond ConfrontationalGame MusicCondition PostMusic[…¹ PreMu…² Impro…³
## <dbl> <dbl> <lgl> <fct> <dbl> <dbl> <dbl>
## 1 1 2 FALSE Exciting -0.0751 0.262 -0.337
## 2 1 2 TRUE Exciting -0.205 0.739 -0.944
## 3 3 1 FALSE Anger -0.732 -2.86 2.13
## 4 3 1 TRUE Anger 0.313 -0.150 0.463
## 5 4 4 FALSE Anger 1.48 1.71 -0.228
## 6 4 4 TRUE Anger -0.205 -1.68 1.47
## 7 5 5 FALSE Exciting 1.24 0.311 0.926
## 8 5 5 TRUE Exciting 0.313 0.231 0.0820
## 9 6 6 FALSE Neutral 0.710 0.960 -0.250
## 10 6 6 TRUE Neutral 0.442 0.866 -0.424
## # … with 166 more rows, and abbreviated variable names ¹PostMusic[,1],
## # ²PreMusic[,1], ³ImprovementScore[,1]If you don’t understand every step of that code (or any other
dplyr code), it can be helpful to look at the result of
running just the first line, then just the first two lines, and so
on.
Now we’re finally to reproduce Fig. 2 from Tamir et al., we just need
to get the mean differences within each game and each kind of music, and
save them to a variable called MeanImprovementScore:
performance_diff_summary_d = performance_diff_d %>%
group_by(MusicCondition, ConfrontationalGame) %>%
mutate(MeanImprovementScore=mean(ImprovementScore, na.rm=T))Let’s take a look at your result (if it has NA values,
how can you fix it?):
performance_diff_summary_d## # A tibble: 176 × 8
## # Groups: MusicCondition, ConfrontationalGame [6]
## Subject Cond ConfrontationalGame MusicCond…¹ PostM…² PreMu…³ Impro…⁴ MeanI…⁵
## <dbl> <dbl> <lgl> <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 FALSE Exciting -0.0751 0.262 -0.337 -0.0182
## 2 1 2 TRUE Exciting -0.205 0.739 -0.944 0.169
## 3 3 1 FALSE Anger -0.732 -2.86 2.13 -0.179
## 4 3 1 TRUE Anger 0.313 -0.150 0.463 0.0612
## 5 4 4 FALSE Anger 1.48 1.71 -0.228 -0.179
## 6 4 4 TRUE Anger -0.205 -1.68 1.47 0.0612
## 7 5 5 FALSE Exciting 1.24 0.311 0.926 -0.0182
## 8 5 5 TRUE Exciting 0.313 0.231 0.0820 0.169
## 9 6 6 FALSE Neutral 0.710 0.960 -0.250 0.114
## 10 6 6 TRUE Neutral 0.442 0.866 -0.424 -0.225
## # … with 166 more rows, and abbreviated variable names ¹MusicCondition,
## # ²PostMusic[,1], ³PreMusic[,1], ⁴ImprovementScore[,1], ⁵MeanImprovementScoreand plot it!
ggplot(performance_diff_summary_d, aes(x=ConfrontationalGame, y=MeanImprovementScore, fill=MusicCondition)) +
geom_bar(position="dodge", stat="identity") +
scale_fill_brewer(palette="Set1")
(Bonus: also calculate the SEM in the summary data, and then add
errorbars to the plot with geom_errorbar!)
Not quite as exact a replication of the effect as Fig. 1. This concurs with the replication report, which says that the hypothesis 1 effect replicated, but hypothesis 2 did not. Here’s a model just for thoroughness (again, don’t worry too much about it):
performance_model = lm(ImprovementScore ~ ConfrontationalGame * MusicCondition, performance_diff_d)
summary(performance_model)##
## Call:
## lm(formula = ImprovementScore ~ ConfrontationalGame * MusicCondition,
## data = performance_diff_d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.5402 -0.6284 -0.0744 0.6253 2.8550
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) -0.1786 0.1895 -0.942
## ConfrontationalGameTRUE 0.2398 0.2760 0.869
## MusicConditionExciting 0.1603 0.2657 0.603
## MusicConditionNeutral 0.2926 0.2657 1.101
## ConfrontationalGameTRUE:MusicConditionExciting -0.0530 0.3815 -0.139
## ConfrontationalGameTRUE:MusicConditionNeutral -0.5786 0.3800 -1.523
## Pr(>|t|)
## (Intercept) 0.347
## ConfrontationalGameTRUE 0.386
## MusicConditionExciting 0.547
## MusicConditionNeutral 0.272
## ConfrontationalGameTRUE:MusicConditionExciting 0.890
## ConfrontationalGameTRUE:MusicConditionNeutral 0.130
##
## Residual standard error: 1.003 on 164 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.02179, Adjusted R-squared: -0.008033
## F-statistic: 0.7306 on 5 and 164 DF, p-value: 0.6014