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, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionlibrary(stringr) # useful for some string manipulation
library(ggplot2)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)
## your code here
min(d[25][0])Warning in min(structure(logical(0), dim = c(91L, 0L), dimnames = list(NULL, :
no non-missing arguments to min; returning Inf[1] InfHighest number: [7] Lowest number: [1]
First, we’ll get rid of rows and columns of the data that we don’t need.
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.)
filtered_d = d %>%
filter(is.na(DoNotUse)) # your code here: exclude subjects that are marked as "DoNotUse"
filtered_d Subject Cond Exper
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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
82 default.mlp 13644374400 62243 7 7 7
83 default.mlp 13644374400 61618 2 5 4
84 default.mlp 13644633600 33161 4 3 6
85 default.mlp 13644633600 40065 1 3 4
86 default.mlp 13644633600 51237 7 7 5
87 default.mlp 13644633600 54293 7 6 6
88 default.mlp 13644633600 58190 5 5 5
Game1AngryFriends Game1AngryStrangers Game1CalmFriends Game1CalmStrangers
1 2 5 2 2
2 2 2 2 2
3 6 6 2 1
4 6 6 2 2
5 3 4 5 4
6 2 6 6 1
7 3 6 1 3
8 7 7 4 5
9 6 6 2 2
10 3 5 1 2
11 7 7 3 3
12 3 6 2 2
13 5 6 2 1
14 2 6 2 6
15 4 7 2 1
16 6 6 2 2
17 5 6 2 3
18 2 6 1 2
19 6 7 2 2
20 1 1 1 1
21 7 7 2 2
22 3 5 1 1
23 4 5 2 2
24 1 1 7 7
25 5 5 3 2
26 2 2 2 1
27 6 7 2 1
28 5 5 2 3
29 5 6 3 3
30 1 3 2 2
31 5 7 2 2
32 3 6 3 6
33 5 6 4 4
34 6 5 2 2
35 1 7 4 5
36 1 1 6 5
37 6 7 2 2
38 6 6 3 3
39 3 7 1 2
40 5 7 2 2
41 5 7 1 1
42 3 4 5 3
43 5 5 3 3
44 2 4 3 1
45 4 4 4 4
46 5 7 4 3
47 4 5 4 4
48 5 7 2 1
49 5 7 2 1
50 2 3 5 4
51 2 4 4 3
52 6 6 3 3
53 7 7 1 1
54 1 1 3 3
55 1 4 1 1
56 2 1 4 4
57 5 7 2 2
58 6 7 1 2
59 2 6 1 2
60 4 7 2 4
61 3 7 2 2
62 3 6 4 6
63 1 1 4 4
64 1 1 3 3
65 1 1 3 3
66 4 7 1 4
67 6 4 3 2
68 6 6 1 1
69 6 4 3 1
70 2 6 1 1
71 2 7 2 2
72 2 7 4 2
73 6 7 2 2
74 7 7 1 5
75 2 5 2 2
76 5 7 2 4
77 3 3 2 4
78 1 4 1 1
79 6 5 4 5
80 5 6 3 1
81 1 6 2 1
82 4 7 1 1
83 1 1 1 1
84 2 3 2 2
85 6 7 1 1
86 4 1 4 4
87 7 5 3 2
88 7 7 1 1
Game1ExcitedFriends Game1ExcitedStrangers Game1Exciting1 Game1Exciting2
1 1 2 3 2
2 2 2 2 3
3 3 4 5 4
4 5 5 1 3
5 6 4 3 2
6 1 1 1 4
7 2 2 4 3
8 3 2 3 4
9 5 5 6 3
10 2 3 1 5
11 4 5 4 4
12 3 3 2 5
13 3 4 2 2
14 6 2 2 6
15 1 3 3 1
16 3 1 1 1
17 3 3 5 5
18 2 6 3 2
19 4 4 2 1
20 2 2 5 5
21 2 4 2 1
22 1 2 4 1
23 5 6 2 4
24 5 5 7 4
25 5 1 3 2
26 6 3 1 1
27 4 2 3 2
28 4 2 1 6
29 4 4 6 5
30 2 2 1 2
31 3 4 2 1
32 3 5 6 6
33 2 1 1 5
34 4 4 3 2
35 2 6 1 1
36 4 4 1 4
37 2 2 2 1
38 3 3 6 4
39 4 6 1 3
40 6 4 4 3
41 2 2 3 2
42 5 5 3 4
43 4 4 5 2
44 5 5 6 5
45 4 4 1 1
46 2 2 4 2
47 5 5 4 3
48 1 2 3 2
49 3 2 6 3
50 5 5 4 2
51 6 5 6 2
52 4 4 1 1
53 5 4 2 4
54 3 1 4 2
55 1 2 2 2
56 3 6 1 1
57 4 4 4 3
58 5 4 3 3
59 2 2 3 2
60 1 2 6 2
61 2 2 1 1
62 5 5 3 3
63 6 5 1 1
64 5 5 3 1
65 4 3 1 4
66 3 5 3 3
67 5 3 5 5
68 1 1 1 1
69 5 6 3 5
70 3 5 1 2
71 2 2 5 5
72 7 4 1 1
73 4 3 1 2
74 1 2 1 2
75 4 4 2 1
76 5 6 4 3
77 6 6 2 2
78 1 1 1 1
79 5 3 1 2
80 5 4 2 1
81 7 7 6 1
82 1 3 3 1
83 1 1 1 1
84 5 5 3 4
85 1 1 1 1
86 7 4 7 7
87 7 6 3 5
88 4 1 1 1
Game1Exciting3 Game1Intro Game1Neutral1 Game1Neutral2 Game1Neutral3
1 6 ok 2 4 4
2 4 ok 1 2 3
3 5 ok 1 2 2
4 2 ok 3 2 4
5 4 ok 2 2 4
6 1 ok 1 1 1
7 4 ok 2 2 2
8 2 ok 2 1 1
9 4 ok 1 2 1
10 1 ok 1 1 2
11 5 ok 1 1 1
12 2 ok 1 2 5
13 2 ok 2 1 1
14 2 ok 5 4 6
15 3 ok 1 1 2
16 1 ok 3 2 1
17 3 ok 2 3 1
18 6 ok 1 1 1
19 2 ok 1 1 1
20 4 ok 1 1 2
21 2 ok 1 1 1
22 4 ok 1 1 1
23 6 ok 1 2 2
24 7 ok 1 4 3
25 2 ok 1 2 4
26 1 ok 1 1 1
27 2 ok 1 1 1
28 2 ok 2 2 3
29 2 ok 2 5 1
30 1 ok 1 4 3
31 2 ok 1 1 1
32 4 ok 5 2 3
33 1 ok 2 3 5
34 2 ok 2 2 1
35 1 ok 3 5 2
36 2 ok 3 6 3
37 1 ok 1 1 2
38 4 ok 1 2 2
39 3 ok 2 3 4
40 5 ok 2 3 1
41 3 ok 1 1 1
42 3 ok 3 2 2
43 6 ok 3 4 2
44 6 ok 1 1 1
45 1 ok 1 7 7
46 3 ok 3 2 5
47 4 ok 3 3 3
48 7 ok 1 1 3
49 5 ok 1 2 2
50 2 ok 2 3 3
51 7 ok 3 1 1
52 1 ok 1 1 1
53 3 ok 2 1 1
54 4 ok 4 1 2
55 2 ok 2 2 2
56 1 ok 1 1 1
57 2 ok 2 5 3
58 4 ok 3 2 1
59 4 ok 4 2 1
60 3 ok 1 2 4
61 1 ok 1 1 1
62 2 ok 2 3 2
63 4 ok 2 1 1
64 1 ok 7 7 2
65 3 ok 3 4 1
66 4 ok 2 2 2
67 2 ok 1 3 2
68 1 ok 1 1 1
69 1 ok 1 1 1
70 1 ok 1 2 6
71 3 ok 3 3 2
72 1 ok 1 1 1
73 3 ok 1 1 2
74 1 ok 1 1 1
75 1 ok 1 1 1
76 2 ok 1 2 2
77 1 ok 3 1 3
78 1 ok 1 1 1
79 3 ok 1 3 4
80 4 ok 1 1 1
81 1 ok 1 1 1
82 5 ok 1 1 2
83 3 ok 2 1 2
84 2 ok 3 3 2
85 1 ok 2 2 3
86 6 ok 2 1 1
87 2 ok 1 2 1
88 1 ok 1 1 6
Game2Angry1 Game2Angry2 Game2Angry3 Game2AngryFriends Game2AngryStrangers
1 6 4 6 3 6
2 5 3 6 3 3
3 6 2 6 3 6
4 5 6 6 5 6
5 6 5 6 3 5
6 7 6 1 1 1
7 5 5 4 2 5
8 1 1 2 1 7
9 6 5 6 6 7
10 6 5 4 5 6
11 7 7 4 6 7
12 7 7 3 6 5
13 2 5 5 2 6
14 6 1 5 2 6
15 1 4 6 3 6
16 5 3 6 5 7
17 7 7 6 4 6
18 6 7 6 4 7
19 4 4 7 6 7
20 4 2 4 1 2
21 4 5 5 7 7
22 4 4 3 2 5
23 1 6 5 7 6
24 7 4 5 1 1
25 5 7 6 6 5
26 5 1 4 3 2
27 6 7 7 5 5
28 4 1 6 2 6
29 5 6 2 7 7
30 5 5 3 1 4
31 7 6 5 6 7
32 6 5 7 6 4
33 4 5 4 4 4
34 5 4 4 4 5
35 5 1 7 1 7
36 1 1 7 1 1
37 6 7 5 6 7
38 5 6 7 6 7
39 6 6 5 4 6
40 6 6 6 5 7
41 3 2 7 5 7
42 5 5 5 6 4
43 6 5 4 6 5
44 5 6 2 4 6
45 3 2 5 4 4
46 5 5 4 7 7
47 7 6 4 5 5
48 6 6 7 7 7
49 5 3 4 6 5
50 5 2 5 3 3
51 6 6 6 2 6
52 5 6 3 5 6
53 6 6 5 7 7
54 5 1 5 1 1
55 4 4 3 2 3
56 6 5 6 1 1
57 7 7 7 6 6
58 5 5 4 5 5
59 6 7 7 3 6
60 6 5 4 5 7
61 7 7 4 2 6
62 5 4 6 2 5
63 7 6 6 1 2
64 6 3 7 7 1
65 4 1 3 4 1
66 5 5 6 4 7
67 5 7 7 7 5
68 5 7 1 6 7
69 4 6 4 7 5
70 6 7 5 2 2
71 4 3 4 5 6
72 4 7 2 3 7
73 6 6 5 5 5
74 5 6 2 7 6
75 4 6 4 5 6
76 6 2 6 6 7
77 1 1 6 5 6
78 5 1 4 1 2
79 3 4 7 4 6
80 4 5 6 5 6
81 7 7 5 6 7
82 7 7 7 1 6
83 1 1 3 1 1
84 4 4 6 2 5
85 5 5 7 1 7
86 7 7 4 1 1
87 6 4 6 7 2
88 5 1 7 7 7
Game2CalmFriends Game2CalmStrangers Game2ExcitedFriends
1 1 2 1
2 3 3 3
3 1 1 2
4 1 1 4
5 3 2 5
6 1 1 1
7 1 2 2
8 7 1 4
9 1 2 4
10 2 2 4
11 1 3 5
12 1 2 3
13 2 3 4
14 3 3 4
15 1 2 3
16 1 1 1
17 2 4 5
18 2 1 5
19 2 2 4
20 1 1 1
21 2 2 4
22 1 1 1
23 2 2 5
24 7 5 5
25 2 2 4
26 5 3 6
27 1 2 2
28 1 3 2
29 3 2 3
30 3 1 2
31 1 2 3
32 2 2 1
33 2 3 2
34 1 2 6
35 3 4 4
36 6 3 3
37 2 2 2
38 3 3 5
39 2 2 3
40 4 2 3
41 2 1 2
42 5 4 4
43 3 4 5
44 3 2 1
45 4 4 4
46 1 1 4
47 4 4 4
48 1 2 1
49 1 1 3
50 4 3 4
51 4 2 5
52 3 2 2
53 1 1 4
54 3 1 2
55 1 1 1
56 3 1 2
57 2 2 3
58 2 1 7
59 1 1 1
60 2 3 1
61 1 5 1
62 6 5 4
63 4 4 5
64 7 6 1
65 3 3 3
66 1 3 2
67 3 2 6
68 1 1 1
69 3 1 5
70 4 2 7
71 3 3 3
72 4 4 6
73 1 1 3
74 1 1 2
75 2 2 4
76 2 4 3
77 6 3 5
78 1 1 1
79 4 5 3
80 2 1 4
81 1 1 1
82 1 1 1
83 1 1 1
84 1 1 5
85 4 4 2
86 5 6 7
87 3 1 7
88 1 1 1
Game2ExcitedStrangers Game2Exciting1 Game2Exciting2 Game2Exciting3
1 1 3 2 4
2 3 2 5 2
3 4 3 2 2
4 4 1 2 2
5 4 2 2 3
6 1 1 1 1
7 4 3 3 3
8 1 1 1 1
9 3 7 3 5
10 4 1 1 1
11 5 6 4 4
12 4 1 2 1
13 4 2 1 2
14 2 3 7 6
15 4 2 1 2
16 1 1 2 1
17 4 2 1 1
18 6 2 2 1
19 4 1 1 1
20 1 4 3 2
21 2 6 1 1
22 3 1 2 5
23 2 2 4 3
24 6 1 1 1
25 3 2 3 4
26 4 1 1 1
27 4 4 5 2
28 3 2 3 1
29 2 5 6 2
30 1 6 2 1
31 5 3 2 1
32 4 6 5 3
33 6 4 7 1
34 1 2 2 2
35 7 1 1 1
36 6 1 1 2
37 2 1 1 1
38 5 4 3 3
39 5 1 4 4
40 3 2 1 2
41 3 1 3 1
42 3 6 5 4
43 5 3 3 4
44 2 5 5 3
45 4 1 2 1
46 3 2 2 3
47 5 2 2 1
48 1 4 1 1
49 2 2 1 1
50 4 2 3 2
51 3 2 2 3
52 3 1 1 1
53 4 2 4 4
54 2 1 1 2
55 1 3 2 3
56 1 1 2 1
57 4 3 3 2
58 6 2 2 2
59 1 1 1 1
60 4 4 2 1
61 1 1 1 1
62 4 3 2 2
63 4 3 3 2
64 5 2 1 1
65 3 3 2 1
66 5 4 4 3
67 5 3 3 2
68 5 1 1 1
69 5 3 1 3
70 7 6 2 1
71 2 4 6 3
72 7 3 1 4
73 4 2 2 4
74 2 2 1 1
75 1 1 1 5
76 4 4 5 5
77 4 1 1 1
78 1 1 1 1
79 5 1 4 4
80 5 2 2 2
81 2 3 1 1
82 1 2 1 2
83 1 1 1 1
84 5 1 2 3
85 2 5 1 1
86 4 7 1 1
87 5 1 3 1
88 4 3 2 2
Game2Intro Game2Neutral1 Game2Neutral2 Game2Neutral3 Game3Angry1 Game3Angry2
1 ok 1 3 1 2 2
2 ok 4 3 1 2 2
3 ok 1 1 3 2 1
4 ok 4 4 5 3 5
5 ok 2 3 4 2 2
6 ok 1 1 1 1 3
7 ok 1 1 1 2 1
8 ok 1 1 1 1 1
9 ok 1 3 1 6 4
10 ok 1 1 1 1 1
11 ok 1 1 1 5 1
12 ok 1 2 3 4 2
13 ok 1 1 1 3 4
14 ok 3 6 5 2 1
15 ok 1 1 4 1 2
16 ok 1 1 1 3 1
17 ok 1 1 1 2 2
18 ok 1 1 1 2 1
19 ok 1 1 1 4 2
20 ok 1 1 1 1 1
21 ok 1 1 1 4 3
22 ok 1 1 1 1 2
23 ok 1 2 1 1 4
24 ok 1 5 3 3 1
25 ok 1 3 2 1 2
26 ok 1 1 1 3 1
27 ok 1 1 1 4 2
28 ok 1 3 2 1 1
29 ok 2 2 1 4 3
30 ok 1 2 1 2 5
31 ok 1 1 1 4 1
32 ok 1 2 3 2 3
33 ok 1 1 1 3 2
34 ok 1 2 1 4 1
35 ok 3 2 3 4 1
36 ok 2 4 1 1 1
37 ok 1 1 1 1 1
38 ok 4 1 5 5 4
39 ok 1 2 5 6 6
40 ok 1 2 3 4 2
41 ok 1 1 1 1 3
42 ok 3 3 3 4 3
43 ok 3 4 2 2 2
44 ok 2 2 3 6 6
45 ok 1 3 6 4 2
46 ok 2 1 3 1 1
47 ok 4 2 2 3 2
48 ok 2 3 3 1 1
49 ok 2 1 1 1 2
50 ok 2 3 2 3 4
51 ok 3 1 1 3 1
52 ok 1 2 2 1 1
53 ok 1 1 1 3 3
54 ok 3 1 2 1 1
55 ok 2 2 2 2 2
56 ok 1 1 3 4 1
57 ok 2 4 1 5 5
58 ok 1 1 1 3 3
59 ok 3 3 1 1 1
60 ok 1 1 1 4 1
61 ok 1 1 1 5 1
62 ok 2 5 6 4 2
63 ok 2 4 2 2 1
64 ok 7 7 1 1 1
65 ok 6 6 2 1 1
66 ok 2 3 2 6 4
67 ok 1 2 1 1 2
68 ok 1 1 1 1 1
69 ok 2 1 1 1 1
70 ok 2 2 5 4 6
71 ok 2 2 2 5 2
72 ok 1 1 1 2 2
73 ok 1 2 1 2 2
74 ok 1 1 1 2 1
75 ok 1 1 1 3 3
76 ok 1 1 2 4 3
77 ok 1 1 3 1 1
78 ok 1 3 1 1 1
79 ok 2 3 6 3 3
80 ok 1 2 4 6 6
81 ok 1 1 1 7 3
82 ok 1 1 2 3 1
83 ok 1 1 1 3 4
84 ok 2 2 1 3 3
85 ok 1 1 1 5 3
86 ok 1 1 1 2 1
87 ok 1 2 2 2 4
88 ok 1 3 1 1 1
Game3Angry3 Game3AngryFriends Game3AngryStrangers Game3CalmFriends
1 3 3 2 7
2 3 4 4 3
3 6 5 4 2
4 6 1 3 5
5 5 1 1 4
6 1 1 1 7
7 6 1 3 6
8 5 4 3 6
9 7 2 2 4
10 5 2 2 4
11 3 3 2 7
12 7 3 5 3
13 6 2 2 5
14 6 1 1 7
15 4 2 1 6
16 4 5 6 2
17 7 4 3 5
18 6 1 1 4
19 2 2 2 5
20 3 1 1 4
21 6 1 1 4
22 5 1 1 2
23 7 3 5 5
24 7 1 1 7
25 5 1 1 5
26 7 3 2 3
27 7 1 1 5
28 4 2 2 6
29 6 4 2 2
30 5 2 2 6
31 6 1 1 6
32 5 2 2 5
33 5 1 1 7
34 6 2 3 5
35 1 4 4 4
36 3 1 1 6
37 7 2 1 3
38 7 3 4 4
39 5 5 3 6
40 6 1 7 5
41 7 1 2 5
42 7 3 4 5
43 3 3 3 5
44 2 2 4 1
45 5 4 4 4
46 7 4 3 6
47 6 3 3 5
48 3 1 1 4
49 6 2 1 4
50 6 2 2 5
51 5 2 3 6
52 3 1 1 4
53 7 2 4 4
54 5 1 1 3
55 4 2 1 5
56 7 2 3 2
57 7 1 2 5
58 6 1 1 4
59 7 1 1 4
60 5 3 1 4
61 6 1 2 5
62 7 2 2 6
63 1 1 1 4
64 7 1 1 7
65 5 1 1 2
66 6 4 4 5
67 7 1 1 5
68 5 1 1 3
69 7 2 1 7
70 5 2 2 4
71 7 1 1 4
72 5 1 2 5
73 6 1 2 4
74 6 1 1 6
75 6 1 1 6
76 3 4 1 6
77 6 3 6 3
78 6 1 1 4
79 7 4 4 6
80 7 4 3 3
81 5 1 1 7
82 7 1 1 7
83 5 2 2 2
84 6 2 2 4
85 6 1 2 5
86 7 1 1 7
87 4 1 1 6
88 5 2 2 7
Game3CalmStrangers Game3ExcitedFriends Game3ExcitedStrangers Game3Exciting1
1 6 6 5 2
2 3 4 4 3
3 2 5 6 3
4 5 6 5 3
5 3 4 2 1
6 5 7 6 1
7 5 6 5 2
8 1 6 3 1
9 3 5 4 4
10 3 6 6 1
11 6 4 6 5
12 2 6 5 3
13 4 5 5 3
14 7 7 7 3
15 4 5 4 2
16 2 3 3 3
17 5 4 3 1
18 3 5 4 2
19 5 4 5 3
20 4 4 4 4
21 4 7 7 4
22 2 5 3 3
23 2 4 4 5
24 7 5 5 2
25 5 3 4 5
26 2 6 4 2
27 3 6 3 1
28 6 4 4 2
29 3 5 4 2
30 3 5 4 2
31 6 4 2 2
32 5 5 5 5
33 7 7 7 1
34 5 5 5 4
35 4 4 5 2
36 5 4 4 1
37 2 5 3 1
38 4 5 3 5
39 4 7 4 1
40 1 6 4 3
41 4 6 6 5
42 4 5 5 3
43 5 4 4 3
44 5 5 6 2
45 4 4 4 2
46 7 7 7 1
47 5 6 5 2
48 5 5 7 2
49 4 5 6 2
50 5 5 6 3
51 5 6 6 4
52 5 6 6 1
53 5 5 5 2
54 3 2 1 1
55 4 4 2 2
56 2 1 1 5
57 4 7 5 2
58 5 4 4 2
59 4 6 4 3
60 4 7 5 4
61 4 6 6 2
62 6 4 5 2
63 4 5 5 1
64 7 3 2 1
65 2 5 6 1
66 6 6 6 4
67 4 3 2 6
68 3 7 5 1
69 6 5 2 1
70 5 5 5 1
71 5 5 6 4
72 5 7 7 2
73 2 5 4 2
74 7 5 4 1
75 6 6 6 2
76 3 7 4 5
77 3 6 6 1
78 6 5 4 1
79 4 4 5 1
80 2 6 5 3
81 7 5 7 3
82 7 5 1 1
83 3 4 2 1
84 4 5 5 2
85 6 4 2 1
86 2 7 3 2
87 4 3 6 5
88 6 7 7 2
Game3Exciting2 Game3Exciting3 Game3Intro Game3Neutral1 Game3Neutral2
1 2 3 ok 5 6
2 6 2 ok 2 3
3 1 3 ok 2 2
4 1 3 ok 2 4
5 2 2 ok 5 4
6 1 4 ok 6 6
7 2 3 ok 1 2
8 2 2 ok 1 3
9 4 2 ok 2 2
10 1 1 ok 2 1
11 3 7 ok 2 2
12 1 2 ok 3 4
13 5 3 ok 2 2
14 6 3 ok 7 6
15 1 3 ok 1 2
16 3 3 ok 4 6
17 1 1 ok 3 2
18 5 3 ok 2 2
19 4 3 ok 3 4
20 1 5 ok 1 1
21 1 4 ok 2 1
22 2 2 ok 2 2
23 5 2 ok 6 6
24 2 2 ok 6 5
25 4 2 ok 1 4
26 2 4 ok 1 1
27 3 1 ok 7 2
28 3 2 ok 5 4
29 2 1 ok 3 2
30 1 2 ok 4 2
31 3 1 ok 1 2
32 7 6 ok 6 5
33 3 3 ok 3 1
34 2 2 ok 3 5
35 3 5 ok 6 7
36 1 1 ok 4 4
37 1 1 ok 1 1
38 5 5 ok 2 5
39 1 2 ok 4 3
40 5 6 ok 2 2
41 2 5 ok 4 5
42 2 2 ok 3 1
43 3 3 ok 5 5
44 6 2 ok 3 2
45 2 1 ok 2 6
46 1 1 ok 4 4
47 2 1 ok 3 2
48 5 5 ok 6 6
49 2 3 ok 3 4
50 5 4 ok 4 6
51 4 6 ok 6 5
52 3 1 ok 5 6
53 2 2 ok 3 2
54 1 4 ok 4 1
55 2 4 ok 4 3
56 1 1 ok 1 1
57 2 3 ok 3 5
58 3 4 ok 2 1
59 3 1 ok 5 6
60 2 4 ok 1 2
61 1 1 ok 1 3
62 2 6 ok 5 5
63 3 6 ok 3 2
64 1 1 ok 3 7
65 3 1 ok 2 4
66 3 3 ok 2 2
67 2 6 ok 1 7
68 1 1 ok 4 5
69 3 1 ok 6 6
70 3 1 ok 2 2
71 4 3 ok 2 2
72 1 4 ok 1 2
73 2 1 ok 3 1
74 1 1 ok 1 4
75 1 3 ok 1 1
76 6 3 ok 4 4
77 1 1 ok 3 4
78 1 1 ok 1 1
79 1 3 ok 1 2
80 2 2 ok 2 1
81 2 1 ok 4 1
82 1 1 ok 3 1
83 2 3 ok 1 1
84 4 2 ok 3 1
85 1 1 ok 5 1
86 1 1 ok 4 6
87 5 6 ok 4 1
88 1 1 ok 4 4
Game3Neutral3 Game4Angry1 Game4Angry2 Game4Angry3 Game4AngryFriends
1 5 2 2 2 2
2 3 5 2 2 4
3 6 1 1 2 1
4 5 3 4 3 2
5 4 2 3 3 1
6 7 1 3 1 1
7 4 1 2 3 2
8 1 7 7 1 2
9 1 3 5 5 2
10 4 1 5 1 1
11 1 1 2 1 1
12 3 3 4 2 2
13 5 5 6 4 2
14 7 1 1 2 2
15 6 1 2 3 2
16 7 4 3 2 1
17 6 6 5 3 3
18 2 1 1 2 1
19 4 4 3 3 1
20 4 1 1 2 1
21 1 2 4 1 1
22 4 1 1 2 1
23 7 1 2 3 4
24 6 3 1 3 1
25 7 1 1 2 2
26 1 1 6 1 2
27 1 2 2 3 2
28 7 1 1 1 1
29 3 1 3 1 3
30 3 3 2 3 4
31 4 5 3 3 2
32 4 4 1 4 3
33 4 5 2 4 2
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
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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
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34 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
35 C:\\Users\\msplab\\Desktop\\Study 151\\Study151Part2.exp default.mlp
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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
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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
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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
21 1 1 1 2
22 3 1 1 4
23 1 2 1 5
24 1 1 1 1
25 1 2 1 4
26 1 1 1 5
27 1 1 1 5
28 1 1 1 5
29 2 2 3 2
30 2 1 1 3
31 1 2 2 5
32 3 3 2 5
33 3 1 1 1
34 2 2 1 4
35 4 3 1 4
36 3 2 2 5
37 3 2 2 4
38 1 2 3 4
39 1 1 2 3
40 2 2 1 5
41 2 1 1 3
42 2 1 2 4
43 3 2 1 4
44 1 1 1 4
45 2 2 2 4
46 2 2 2 4
47 1 1 2 3
48 2 1 2 4
49 2 1 1 4
50 1 1 1 3
51 3 1 1 3
52 1 5 1 3
53 1 1 1 5
54 2 2 2 5
55 2 1 1 3
56 2 2 1 5
57 2 2 1 3
58 4 4 2 5
59 3 1 1 5
60 4 1 1 5
61 2 1 1 3
62 3 1 1 4
63 2 2 1 5
64 1 2 1 3
65 4 2 4 1
66 1 2 3 4
67 2 1 1 5
68 1 1 1 4
69 1 1 1 5
70 1 1 2 4
71 2 2 2 3
72 4 1 1 1
73 1 1 1 5
74 2 1 1 1
75 1 2 2 5
76 1 1 1 4
77 2 2 1 4
78 NA NA NA NA
79 2 1 3 3
80 3 1 1 4
81 2 2 1 4
82 2 1 1 1
83 3 2 1 2
84 1 2 1 4
85 1 1 1 3
86 2 2 1 5
87 1 2 1 5
88 1 1 1 5
HowAngryAngry2 HowAngryAngry3 HowAngryExciting1 HowAngryExciting2
1 4 4 3 4
2 4 4 3 1
3 2 3 1 1
4 2 3 2 2
5 2 2 2 1
6 4 4 2 1
7 4 2 2 1
8 1 1 1 1
9 4 2 2 1
10 4 2 2 1
11 5 3 2 2
12 5 3 4 2
13 3 2 1 1
14 5 4 3 1
15 5 4 2 2
16 3 4 1 1
17 3 3 1 1
18 5 2 1 1
19 4 4 1 2
20 3 2 1 1
21 3 3 1 1
22 4 1 2 2
23 5 3 4 1
24 1 1 1 1
25 5 3 3 3
26 5 4 4 2
27 5 4 3 1
28 5 4 4 2
29 3 2 2 1
30 3 2 2 4
31 5 3 2 1
32 5 4 4 4
33 2 1 2 2
34 3 3 1 2
35 4 3 5 1
36 5 3 2 2
37 3 1 1 1
38 4 3 2 3
39 2 4 4 2
40 4 5 2 4
41 4 2 1 1
42 2 2 4 3
43 4 3 2 3
44 5 5 4 5
45 5 2 1 1
46 4 3 5 5
47 4 4 4 4
48 4 3 3 1
49 4 4 3 2
50 3 1 1 1
51 4 4 3 2
52 3 2 1 1
53 5 2 3 3
54 5 3 3 1
55 3 1 2 2
56 5 4 1 1
57 4 3 3 2
58 5 3 1 2
59 5 5 3 3
60 5 3 1 2
61 5 3 1 1
62 4 3 2 2
63 4 4 4 1
64 5 5 3 4
65 1 2 1 3
66 5 4 2 3
67 5 2 1 1
68 5 3 3 1
69 5 2 2 2
70 5 3 2 1
71 4 1 1 1
72 3 1 1 1
73 5 3 2 1
74 1 3 1 3
75 5 3 1 1
76 3 2 1 1
77 5 3 4 4
78 NA NA NA NA
79 5 2 4 3
80 4 2 2 1
81 5 1 1 1
82 3 1 1 1
83 3 3 2 2
84 5 4 3 2
85 5 1 1 1
86 5 1 3 1
87 5 4 2 3
88 5 3 3 1
HowAngryExciting3 HowAngryNeutral1 HowAngryNeutral2 HowAngryNeutral3
1 3 2 2 1
2 3 1 1 2
3 1 2 1 1
4 1 1 1 1
5 1 1 1 1
6 2 1 1 1
7 2 2 1 1
8 1 1 1 1
9 1 1 2 1
10 1 1 1 1
11 1 1 1 1
12 3 1 1 2
13 1 1 1 1
14 2 1 1 2
15 1 1 1 1
16 1 1 1 1
17 1 1 1 1
18 3 1 1 1
19 2 1 1 1
20 1 1 1 1
21 1 1 1 1
22 1 1 1 1
23 1 1 1 1
24 1 1 1 1
25 5 1 5 1
26 3 3 1 1
27 2 1 1 1
28 1 1 1 1
29 1 1 1 1
30 4 1 2 1
31 2 1 1 1
32 2 3 2 1
33 1 2 1 1
34 2 1 1 1
35 2 1 4 2
36 2 1 1 1
37 1 1 1 1
38 3 2 2 2
39 3 2 1 1
40 4 1 2 1
41 1 1 1 1
42 3 1 3 1
43 5 1 1 1
44 3 2 1 3
45 1 1 1 1
46 4 1 1 1
47 4 1 2 1
48 1 1 1 1
49 2 1 1 1
50 1 1 1 1
51 3 2 1 1
52 1 1 1 1
53 2 1 1 1
54 1 1 1 1
55 2 1 1 1
56 1 1 1 1
57 2 1 1 1
58 2 2 1 1
59 2 1 1 1
60 1 2 1 1
61 1 1 1 1
62 1 1 1 1
63 1 1 1 1
64 4 1 1 1
65 1 4 4 4
66 2 2 2 1
67 1 1 1 1
68 1 1 1 1
69 3 1 1 1
70 1 1 1 3
71 1 1 1 1
72 1 1 1 1
73 1 1 1 1
74 1 4 5 1
75 1 1 1 1
76 1 1 1 1
77 4 2 4 2
78 NA NA NA NA
79 3 4 2 1
80 2 2 1 1
81 1 1 1 1
82 1 1 1 1
83 2 2 2 2
84 1 1 1 1
85 1 1 5 1
86 2 1 1 1
87 1 1 1 1
88 1 1 1 1
HowExcitedAngry1 HowExcitedAngry2 HowExcitedAngry3 HowExcitedExciting1
1 4 3 3 4
2 3 3 2 2
3 4 1 3 4
4 4 4 5 3
5 5 2 3 3
6 5 2 3 3
7 3 3 4 4
8 5 5 5 5
9 4 5 4 4
10 4 4 2 3
11 5 4 3 5
12 4 5 4 4
13 4 4 3 4
14 2 2 3 5
15 2 5 5 4
16 2 4 4 1
17 5 5 4 4
18 5 5 5 3
19 5 4 5 2
20 3 1 2 4
21 4 3 2 5
22 5 5 2 4
23 3 5 4 4
24 5 4 3 4
25 5 3 4 3
26 5 4 5 3
27 5 4 5 3
28 4 4 5 5
29 4 3 3 4
30 3 3 2 4
31 3 3 2 5
32 4 5 5 4
33 4 5 3 5
34 2 4 4 3
35 3 2 3 2
36 4 4 4 5
37 1 1 4 3
38 5 4 3 3
39 4 5 5 3
40 5 5 5 3
41 4 4 4 4
42 4 3 5 4
43 4 4 3 4
44 4 5 4 4
45 1 1 3 2
46 5 5 4 5
47 5 5 4 4
48 3 3 4 3
49 5 4 5 4
50 3 1 3 2
51 4 5 5 5
52 4 4 4 4
53 5 5 5 3
54 2 1 1 3
55 2 1 2 3
56 3 4 4 4
57 4 5 4 3
58 4 4 3 3
59 5 5 5 3
60 4 3 3 5
61 1 1 3 3
62 4 4 4 5
63 5 4 4 4
64 4 4 5 5
65 1 1 1 1
66 3 1 2 1
67 5 4 4 3
68 4 3 4 5
69 1 2 1 4
70 4 5 3 2
71 4 3 5 4
72 5 3 3 5
73 4 4 5 4
74 2 1 3 1
75 3 3 5 2
76 4 3 4 4
77 5 5 3 3
78 NA NA NA NA
79 2 2 3 4
80 4 2 5 4
81 5 4 3 3
82 4 5 2 2
83 2 4 3 1
84 5 5 5 4
85 4 4 4 3
86 5 5 5 5
87 5 5 4 3
88 5 5 5 4
HowExcitedExciting2 HowExcitedExciting3 HowExcitedNeutral1
1 4 4 2
2 2 3 2
3 3 5 2
4 3 3 2
5 2 4 1
6 4 4 1
7 4 4 2
8 5 5 1
9 3 2 2
10 3 3 2
11 4 5 2
12 4 4 2
13 3 4 3
14 5 4 3
15 3 3 1
16 4 1 3
17 5 4 2
18 3 4 1
19 1 2 1
20 4 5 1
21 3 3 1
22 4 5 2
23 5 5 1
24 5 4 1
25 5 5 1
26 5 4 1
27 4 5 2
28 4 5 2
29 4 3 3
30 3 2 2
31 4 1 1
32 3 4 2
33 5 5 1
34 4 2 1
35 4 2 2
36 5 5 2
37 5 4 1
38 3 3 2
39 3 3 1
40 4 5 2
41 4 4 1
42 4 2 2
43 3 4 3
44 3 3 4
45 3 3 1
46 5 5 3
47 3 5 2
48 5 4 2
49 2 5 1
50 2 3 1
51 4 5 4
52 4 4 1
53 4 4 2
54 4 4 3
55 3 3 1
56 3 3 2
57 3 3 1
58 5 4 3
59 5 5 3
60 2 4 3
61 4 5 1
62 5 4 1
63 2 2 2
64 3 3 1
65 3 1 3
66 2 2 3
67 4 3 1
68 5 4 1
69 4 5 1
70 3 3 1
71 4 4 2
72 4 5 2
73 4 5 1
74 3 2 4
75 1 3 2
76 4 5 1
77 3 3 3
78 NA NA NA
79 4 5 2
80 4 4 1
81 4 5 1
82 1 3 1
83 3 3 2
84 4 4 1
85 4 4 1
86 5 5 1
87 4 5 2
88 5 4 1
HowExcitedNeutral2 HowExcitedNeutral3 HowPleasantAngry1 HowPleasantAngry2
1 2 2 1 2
2 1 2 2 2
3 2 1 1 1
4 1 3 4 3
5 1 2 2 2
6 1 1 1 2
7 1 2 1 1
8 2 2 1 1
9 2 1 3 2
10 1 1 1 1
11 1 1 2 1
12 1 3 1 3
13 2 1 2 2
14 4 2 1 1
15 1 1 1 2
16 2 1 2 4
17 1 1 4 2
18 1 1 1 1
19 1 1 2 1
20 1 1 1 1
21 1 1 3 2
22 1 1 1 1
23 1 1 2 1
24 1 1 2 1
25 2 2 1 2
26 1 1 1 1
27 2 1 2 1
28 3 1 1 1
29 3 2 3 2
30 1 2 1 2
31 1 2 1 1
32 3 1 1 1
33 2 1 4 4
34 1 1 1 2
35 3 1 3 3
36 2 2 4 1
37 1 1 2 1
38 2 2 2 1
39 1 2 4 3
40 1 2 2 3
41 3 1 1 1
42 2 2 3 4
43 2 2 2 1
44 1 1 1 1
45 1 1 2 2
46 2 2 4 4
47 1 1 2 2
48 1 2 2 3
49 1 2 1 1
50 1 1 2 1
51 2 1 2 1
52 1 2 2 1
53 2 2 1 2
54 3 3 1 1
55 1 1 2 2
56 2 1 1 1
57 1 1 3 3
58 2 2 2 1
59 2 1 1 3
60 1 1 1 1
61 1 2 2 2
62 1 2 2 1
63 1 2 1 1
64 2 1 2 1
65 4 3 1 1
66 3 5 2 1
67 1 1 1 1
68 1 1 1 1
69 1 1 1 1
70 1 1 1 4
71 1 2 2 1
72 2 1 5 2
73 1 2 2 1
74 4 4 2 1
75 1 1 1 1
76 1 2 2 1
77 2 4 4 5
78 NA NA NA NA
79 3 4 3 2
80 2 1 2 1
81 1 1 5 1
82 1 3 1 1
83 2 2 2 2
84 1 1 2 2
85 2 1 3 3
86 5 5 1 1
87 2 1 3 3
88 1 2 2 1
HowPleasantAngry3 HowPleasantExciting1 HowPleasantExciting2
1 1 2 2
2 4 2 2
3 3 4 4
4 2 1 1
5 3 3 3
6 2 3 3
7 3 1 2
8 5 4 3
9 2 2 4
10 2 1 3
11 3 1 2
12 2 1 2
13 3 2 2
14 2 1 4
15 1 1 1
16 5 2 3
17 3 2 4
18 3 4 4
19 3 2 1
20 2 3 3
21 2 3 2
22 2 1 2
23 2 1 5
24 3 3 3
25 3 1 2
26 2 2 4
27 1 2 2
28 1 1 1
29 4 2 5
30 2 1 2
31 2 4 2
32 4 2 3
33 2 3 5
34 4 4 3
35 2 4 4
36 4 2 3
37 3 1 5
38 1 1 1
39 3 1 3
40 2 3 5
41 1 1 1
42 4 4 3
43 3 3 3
44 1 2 2
45 4 3 3
46 4 5 5
47 2 4 1
48 5 1 3
49 2 1 4
50 3 2 3
51 2 3 3
52 2 4 4
53 4 2 2
54 1 2 3
55 2 2 2
56 2 3 2
57 4 2 3
58 3 4 4
59 1 1 5
60 2 4 4
61 2 4 5
62 2 2 4
63 1 1 1
64 4 3 4
65 3 1 4
66 1 1 1
67 3 2 3
68 5 2 4
69 3 1 3
70 4 2 2
71 2 4 5
72 3 5 4
73 1 2 3
74 3 1 3
75 1 2 3
76 2 3 5
77 3 4 4
78 NA NA NA
79 3 1 2
80 2 3 3
81 2 5 3
82 3 1 2
83 3 1 1
84 2 1 2
85 4 2 4
86 5 5 5
87 2 3 3
88 3 1 5
HowPleasantExciting3 HowPleasantNeutral1 HowPleasantNeutral2
1 1 5 4
2 2 2 2
3 3 2 4
4 2 1 1
5 4 3 3
6 4 4 4
7 3 3 3
8 1 2 3
9 4 3 3
10 2 2 2
11 4 4 3
12 3 5 3
13 2 4 4
14 2 4 5
15 1 3 4
16 3 2 4
17 1 4 4
18 3 5 5
19 1 4 4
20 3 4 5
21 1 3 3
22 2 3 4
23 5 3 1
24 3 5 4
25 2 3 3
26 2 3 4
27 1 5 4
28 3 4 5
29 2 4 5
30 2 3 1
31 4 3 4
32 2 3 4
33 3 5 3
34 4 2 3
35 4 5 4
36 5 5 5
37 3 4 5
38 1 2 3
39 3 2 3
40 4 3 3
41 1 3 4
42 2 2 2
43 3 5 4
44 3 1 2
45 3 3 5
46 5 3 2
47 4 5 4
48 3 4 5
49 2 3 5
50 3 4 3
51 3 4 5
52 4 3 3
53 3 5 5
54 3 4 2
55 3 4 4
56 3 3 1
57 3 5 5
58 5 3 3
59 3 5 3
60 3 2 2
61 5 4 3
62 3 3 4
63 1 2 2
64 4 5 5
65 2 3 2
66 2 2 2
67 4 5 5
68 2 5 5
69 3 2 5
70 1 2 3
71 5 3 3
72 5 3 1
73 2 4 5
74 3 5 4
75 2 5 5
76 5 4 5
77 5 2 2
78 NA NA NA
79 2 5 4
80 3 4 4
81 4 3 1
82 2 5 5
83 1 3 4
84 3 4 5
85 3 3 3
86 2 5 5
87 5 4 4
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
45 47 4 0 4 100
46 48 3 0 3 1100
47 49 3 370 3 920
48 50 3 680 3 1170
49 51 3 0 3 0
50 52 3 0 3 990
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
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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.
The dataset contains a bunch of columns we don’t care about:
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"))Now 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 nameNow 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)
rating_hyp_long_d = rating_hyp_d %>%
pivot_longer(cols=-c("Subject", "Cond"),
names_to='Measurement',
values_to='Score')
head(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
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
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
Game1Neutral1 Game1Neutral2 Game1Neutral3 Game2Angry1 Game2Angry2 Game2Angry3
1 2 4 4 6 4 6
2 1 2 3 5 3 6
3 2 2 4 6 5 6
4 2 1 1 1 1 2
5 1 2 1 6 5 6
6 1 1 2 6 5 4
Game2AngryFriends Game2AngryStrangers Game2CalmFriends Game2CalmStrangers
1 3 6 1 2
2 3 3 3 3
3 3 5 3 2
4 1 7 7 1
5 6 7 1 2
6 5 6 2 2
Game2ExcitedFriends Game2ExcitedStrangers Game2Exciting1 Game2Exciting2
1 1 1 3 2
2 3 3 2 5
3 5 4 2 2
4 4 1 1 1
5 4 3 7 3
6 4 4 1 1
Game2Exciting3 Game2Neutral1 Game2Neutral2 Game2Neutral3 Game3Angry1
1 4 1 3 1 2
2 2 4 3 1 2
3 3 2 3 4 2
4 1 1 1 1 1
5 5 1 3 1 6
6 1 1 1 1 1
Game3Angry2 Game3Angry3 Game3AngryFriends Game3AngryStrangers
1 2 3 3 2
2 2 3 4 4
3 2 5 1 1
4 1 5 4 3
5 4 7 2 2
6 1 5 2 2
Game3CalmFriends Game3CalmStrangers Game3ExcitedFriends Game3ExcitedStrangers
1 7 6 6 5
2 3 3 4 4
3 4 3 4 2
4 6 1 6 3
5 4 3 5 4
6 4 3 6 6
Game3Exciting1 Game3Exciting2 Game3Exciting3 Game3Neutral1 Game3Neutral2
1 2 2 3 5 6
2 3 6 2 2 3
3 1 2 2 5 4
4 1 2 2 1 3
5 4 4 2 2 2
6 1 1 1 2 1
Game3Neutral3 Game4Angry1 Game4Angry2 Game4Angry3 Game4AngryFriends
1 5 2 2 2 2
2 3 5 2 2 4
3 4 2 3 3 1
4 1 7 7 1 2
5 1 3 5 5 2
6 4 1 5 1 1
Game4AngryStrangers Game4CalmFriends Game4CalmStrangers Game4ExcitedFriends
1 2 5 5 7
2 5 2 4 4
3 2 4 4 5
4 1 1 1 4
5 2 1 1 6
6 4 3 4 3
Game4ExcitedStrangers Game4Exciting1 Game4Exciting2 Game4Exciting3
1 4 5 5 2
2 5 7 4 5
3 4 2 4 3
4 1 4 7 3
5 3 5 6 4
6 6 1 4 5
Game4Neutral1 Game4Neutral2 Game4Neutral3
1 1 5 2
2 3 2 4
3 3 5 5
4 6 2 2
5 2 4 2
6 1 5 2The 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 labels
performance_hyp_long_d$Cond [1] 2 2 2 2 1 1 1 1 4 4 4 4 5 5 5 5 6 6 6 6 3 3 3 3 6 6 6 6 5 5 5 5 1 1 1 1 2
[38] 2 2 2 4 4 4 4 4 4 4 4 6 6 6 6 2 2 2 2 3 3 3 3 5 5 5 5 1 1 1 1 4 4 4 4 3 3
[75] 3 3 6 6 6 6 5 5 5 5 2 2 2 2 2 2 2 2 1 1 1 1 3 3 3 3 4 4 4 4 6 6 6 6 5 5 5
[112] 5 4 4 4 4 5 5 5 5 3 3 3 3 1 1 1 1 2 2 2 2 6 6 6 6 1 1 1 1 6 6 6 6 4 4 4 4
[149] 3 3 3 3 5 5 5 5 2 2 2 2 6 6 6 6 2 2 2 2 3 3 3 3 1 1 1 1 4 4 4 4 5 5 5 5 5
[186] 5 5 5 3 3 3 3 4 4 4 4 1 1 1 1 6 6 6 6 2 2 2 2 4 4 4 4 3 3 3 3 2 2 2 2 5 5
[223] 5 5 1 1 1 1 6 6 6 6 3 3 3 3 6 6 6 6 1 1 1 1 2 2 2 2 4 4 4 4 5 5 5 5 4 4 4
[260] 4 3 3 3 3 6 6 6 6 2 2 2 2 5 5 5 5 1 1 1 1 1 1 1 1 2 2 2 2 6 6 6 6 5 5 5 5
[297] 4 4 4 4 3 3 3 3 6 6 6 6 2 2 2 2 5 5 5 5 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 3
[334] 3 3 3 1 1 1 1 6 6 6 6 2 2 2 2 3 3 3 3Now 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),## Your code here
)
unique(rating_hyp_long_d$Cond)[1] 2 1 6 5 4 3rating_hyp_long_d# A tibble: 2,820 × 5
Subject Cond Measurement Score IsRecall
<dbl> <dbl> <chr> <dbl> <lgl>
1 1 2 Game1Angry1 6 FALSE
2 1 2 Game1Angry2 6 FALSE
3 1 2 Game1Angry3 5 FALSE
4 1 2 Game1AngryFriends 2 TRUE
5 1 2 Game1AngryStrangers 5 TRUE
6 1 2 Game1CalmFriends 2 TRUE
7 1 2 Game1CalmStrangers 2 TRUE
8 1 2 Game1ExcitedFriends 1 TRUE
9 1 2 Game1ExcitedStrangers 2 TRUE
10 1 2 Game1Exciting1 3 FALSE
# ℹ 2,810 more rowsHere are a couple other useful ways of manipulating columns. (You won’t remember all the functions you see here now, but that’s okay. You can always reference this tutorial later if there’s something you need to figure out how to do.)
rating_hyp_long_d = rating_hyp_long_d %>%
mutate(
GameNumber = as.numeric(substr(rating_hyp_long_d$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))
)
rating_hyp_long_d$GameNumber [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3
[38] 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[75] 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4
[112] 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2
[149] 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1
[186] 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3
[223] 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2
[260] 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4
[297] 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3
[334] 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1
[371] 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4
[408] 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
[445] 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1
[482] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3
[519] 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[556] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4
[593] 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2
[630] 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1
[667] 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3
[704] 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2
[741] 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4
[778] 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3
[815] 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1
[852] 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4
[889] 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2
[926] 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1
[963] 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3
[1000] 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2
[1037] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4
[1074] 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
[1111] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1
[1148] 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3
[1185] 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2
[1222] 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4
[1259] 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3
[1296] 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1
[1333] 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4
[1370] 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2
[1407] 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1
[1444] 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3
[1481] 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2
[1518] 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4
[1555] 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3
[1592] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1
[1629] 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
[1666] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2
[1703] 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4
[1740] 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3
[1777] 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1
[1814] 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4
[1851] 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2
[1888] 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1
[1925] 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3
[1962] 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2
[1999] 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4
[2036] 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3
[2073] 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1
[2110] 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4
[2147] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2
[2184] 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
[2221] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3
[2258] 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[2295] 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4
[2332] 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2
[2369] 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1
[2406] 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3
[2443] 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2
[2480] 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4
[2517] 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3
[2554] 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1
[2591] 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4
[2628] 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
[2665] 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1
[2702] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3
[2739] 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[2776] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4
[2813] 4 4 4 4 4 4 4 4For 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()
performance_hyp_long_d# A tibble: 352 × 8
Subject Cond Measurement Score ConfrontationalGame WithMusic MusicCondition
<dbl> <dbl> <chr> <dbl> <lgl> <lgl> <fct>
1 1 2 DinerDashWi… 5830 FALSE TRUE Exciting
2 1 2 DinerDashWi… 5000 FALSE FALSE Exciting
3 1 2 SOFMusicEne… 19 TRUE TRUE Exciting
4 1 2 SOFNoMusicE… 22 TRUE FALSE Exciting
5 3 1 DinerDashWi… 5370 FALSE TRUE Anger
6 3 1 DinerDashWi… 1250 FALSE FALSE Anger
7 3 1 SOFMusicEne… 23 TRUE TRUE Anger
8 3 1 SOFNoMusicE… 15 TRUE FALSE Anger
9 4 4 DinerDashWi… 6921 FALSE TRUE Anger
10 4 4 DinerDashWi… 6742 FALSE FALSE Anger
# ℹ 342 more rows
# ℹ 1 more variable: z_scored_performance <dbl[,1]>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.)
rating_summary_d = rating_hyp_long_d %>%
group_by(ConfrontationalGame,Emotion) %>%
summarize(MeanRating = mean(Score, na.rm=T)) ## your code here`summarise()` has grouped output by 'ConfrontationalGame'. You can override
using the `.groups` argument.Let’s take a look at the result:
rating_summary_d# A tibble: 6 × 3
# Groups: ConfrontationalGame [2]
ConfrontationalGame Emotion MeanRating
<lgl> <chr> <dbl>
1 FALSE Angry 2.72
2 FALSE Exciting 3.97
3 FALSE Neutral 3.68
4 TRUE Angry 4.68
5 TRUE Exciting 3.05
6 TRUE Neutral 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(Score ~ ConfrontationalGame * Emotion, rating_hyp_long_d)
summary(model)
Call:
lm(formula = Score ~ 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-16There 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() %>% # 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)
# performance_diff_dperformance_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] PreMusic[,1]
<dbl> <dbl> <lgl> <fct> <dbl> <dbl>
1 1 2 FALSE Exciting -0.0751 0.262
2 1 2 TRUE Exciting -0.205 0.739
3 3 1 FALSE Anger -0.732 -2.86
4 3 1 TRUE Anger 0.313 -0.150
5 4 4 FALSE Anger 1.48 1.71
6 4 4 TRUE Anger -0.205 -1.68
7 5 5 FALSE Exciting 1.24 0.311
8 5 5 TRUE Exciting 0.313 0.231
9 6 6 FALSE Neutral 0.710 0.960
10 6 6 TRUE Neutral 0.442 0.866
# ℹ 166 more rows
# ℹ 1 more variable: ImprovementScore <dbl[,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(ConfrontationalGame,MusicCondition)%>%
summarize(MeanImprovementScore = mean(ImprovementScore,na.rm=T),
StandardErrorScore = sd(ImprovementScore, na.rm = TRUE) / sqrt(sum(!is.na(ImprovementScore))
))`summarise()` has grouped output by 'ConfrontationalGame'. You can override
using the `.groups` argument.performance_diff_summary_d# A tibble: 6 × 4
# Groups: ConfrontationalGame [2]
ConfrontationalGame MusicCondition MeanImprovementScore StandardErrorScore
<lgl> <fct> <dbl> <dbl>
1 FALSE Anger -0.179 0.253
2 FALSE Exciting -0.0182 0.143
3 FALSE Neutral 0.114 0.161
4 TRUE Anger 0.0612 0.179
5 TRUE Exciting 0.169 0.185
6 TRUE Neutral -0.225 0.192rating_hyp_long_d# A tibble: 2,820 × 8
Subject Cond Measurement Score IsRecall GameNumber ConfrontationalGame
<dbl> <dbl> <chr> <dbl> <lgl> <dbl> <lgl>
1 1 2 Game1Angry1 6 FALSE 1 TRUE
2 1 2 Game1Angry2 6 FALSE 1 TRUE
3 1 2 Game1Angry3 5 FALSE 1 TRUE
4 1 2 Game1AngryFriends 2 TRUE 1 TRUE
5 1 2 Game1AngryStrang… 5 TRUE 1 TRUE
6 1 2 Game1CalmFriends 2 TRUE 1 TRUE
7 1 2 Game1CalmStrange… 2 TRUE 1 TRUE
8 1 2 Game1ExcitedFrie… 1 TRUE 1 TRUE
9 1 2 Game1ExcitedStra… 2 TRUE 1 TRUE
10 1 2 Game1Exciting1 3 FALSE 1 TRUE
# ℹ 2,810 more rows
# ℹ 1 more variable: Emotion <chr>performance_diff_d# A tibble: 176 × 7
Subject Cond ConfrontationalGame MusicCondition PostMusic[,1] PreMusic[,1]
<dbl> <dbl> <lgl> <fct> <dbl> <dbl>
1 1 2 FALSE Exciting -0.0751 0.262
2 1 2 TRUE Exciting -0.205 0.739
3 3 1 FALSE Anger -0.732 -2.86
4 3 1 TRUE Anger 0.313 -0.150
5 4 4 FALSE Anger 1.48 1.71
6 4 4 TRUE Anger -0.205 -1.68
7 5 5 FALSE Exciting 1.24 0.311
8 5 5 TRUE Exciting 0.313 0.231
9 6 6 FALSE Neutral 0.710 0.960
10 6 6 TRUE Neutral 0.442 0.866
# ℹ 166 more rows
# ℹ 1 more variable: ImprovementScore <dbl[,1]>Let’s take a look at your result (if it has NA values, how can you fix it?):
performance_diff_summary_d# A tibble: 6 × 4
# Groups: ConfrontationalGame [2]
ConfrontationalGame MusicCondition MeanImprovementScore StandardErrorScore
<lgl> <fct> <dbl> <dbl>
1 FALSE Anger -0.179 0.253
2 FALSE Exciting -0.0182 0.143
3 FALSE Neutral 0.114 0.161
4 TRUE Anger 0.0612 0.179
5 TRUE Exciting 0.169 0.185
6 TRUE Neutral -0.225 0.192and plot it!
ggplot(performance_diff_summary_d, aes(x=ConfrontationalGame, y=MeanImprovementScore, fill=MusicCondition)) +
geom_bar(position="dodge", stat="identity") +
geom_errorbar(aes(ymin = MeanImprovementScore - StandardErrorScore,
ymax = MeanImprovementScore + StandardErrorScore),
width = 0.2,
position = position_dodge(0.9))+
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