#setwd("/Users/melissamesinas/Desktop/PSYCH 251/data")
pilot1 <- read.csv("/Users/melissamesinas/Desktop/PSYCH 251/data/Porteretal2016-pilot.csv")head (pilot1)## StartDate
## 1 Start Date
## 2 {"ImportId":"startDate","timeZone":"America/Los_Angeles"}
## 3 10/27/18 22:42
## 4 10/27/18 22:51
## 5 10/28/18 9:02
## 6 10/28/18 11:34
## EndDate
## 1 End Date
## 2 {"ImportId":"endDate","timeZone":"America/Los_Angeles"}
## 3 10/27/18 22:43
## 4 10/27/18 22:51
## 5 10/28/18 9:04
## 6 10/28/18 11:36
## Status IPAddress Progress
## 1 Response Type IP Address Progress
## 2 {"ImportId":"status"} {"ImportId":"ipAddress"} {"ImportId":"progress"}
## 3 IP Address 72.201.244.73 100
## 4 IP Address 72.201.244.73 100
## 5 IP Address 174.238.141.46 100
## 6 IP Address 76.102.93.109 100
## Duration..in.seconds. Finished
## 1 Duration (in seconds) Finished
## 2 {"ImportId":"duration"} {"ImportId":"finished"}
## 3 81 TRUE
## 4 45 TRUE
## 5 101 TRUE
## 6 105 TRUE
## RecordedDate
## 1 Recorded Date
## 2 {"ImportId":"recordedDate","timeZone":"America/Los_Angeles"}
## 3 10/27/18 22:43
## 4 10/27/18 22:51
## 5 10/28/18 9:04
## 6 10/28/18 11:36
## ResponseId RecipientLastName
## 1 Response ID Recipient Last Name
## 2 {"ImportId":"_recordId"} {"ImportId":"recipientLastName"}
## 3 R_3k4FeSJ7j31PnoX
## 4 R_3EGsiYtTYzVUjc6
## 5 R_2CpRHlu3nfMi21J
## 6 R_8omau0i4XvSTIOd
## RecipientFirstName RecipientEmail
## 1 Recipient First Name Recipient Email
## 2 {"ImportId":"recipientFirstName"} {"ImportId":"recipientEmail"}
## 3
## 4
## 5
## 6
## ExternalReference LocationLatitude
## 1 External Data Reference Location Latitude
## 2 {"ImportId":"externalDataReference"} {"ImportId":"locationLatitude"}
## 3 33.4367981
## 4 33.4367981
## 5 33.51229858
## 6 37.539505
## LocationLongitude DistributionChannel
## 1 Location Longitude Distribution Channel
## 2 {"ImportId":"locationLongitude"} {"ImportId":"distributionChannel"}
## 3 -111.7128983 anonymous
## 4 -111.7128983 anonymous
## 5 -112.1417007 anonymous
## 6 -122.2998047 anonymous
## UserLanguage
## 1 User Language
## 2 {"ImportId":"userLanguage"}
## 3 EN
## 4 EN
## 5 EN
## 6 EN
## Q4
## 1 Based on the information you read, what is the likelihood that the communicator describing Peter is a Democrat or a Republican? \nPlease click on the number that best represents your answer.
## 2 {"ImportId":"QID4"}
## 3
## 4 4
## 5 5
## 6 5
## Q5
## 1 Based on the information in the passage on the last page, in what percentage of future situations do you think Peter is likely to be helpful?
## 2 {"ImportId":"QID5_TEXT"}
## 3 80
## 4 90
## 5 80
## 6 85
## Q6
## 1 Based on the information in the passage on the last page, in what percentage of future situations do you think Peter is likely to be rude?
## 2 {"ImportId":"QID6_TEXT"}
## 3 10
## 4 76
## 5 70
## 6 15
## Q12
## 1 What is your gender?
## 2 {"ImportId":"QID12"}
## 3 Female
## 4 Female
## 5 Female
## 6 Female
## Q13
## 1 Generally speaking, do you usually consider yourself a Democrat, Republican, an Independent, or affiliated with another political party?
## 2 {"ImportId":"QID13"}
## 3 Democrat
## 4 Republican
## 5 Independent
## 6 Democrat
## Q14
## 1 Please indicate how much you agree or disagree with the following statement: \nI endorse many aspects of conservative political ideology.
## 2 {"ImportId":"QID14"}
## 3 Strongly disagree
## 4 Strongly disagree
## 5 Agree
## 6 Disagree
## Q15
## 1 Please indicate how much you agree or disagree with the following statement: \nI endorse many aspects of liberal political ideology.
## 2 {"ImportId":"QID15"}
## 3 Agree
## 4 Disagree
## 5 Agree
## 6 Agree
## Q16
## 1 In general, how would you describe your political views on social issues?
## 2 {"ImportId":"QID16"}
## 3 Somewhat liberal
## 4 Somewhat conservative
## 5 Very conservative
## 6 Very liberallibrary(tidyverse)## ── Attaching packages ────── tidyverse 1.2.1 ──## ✔ ggplot2 3.0.0 ✔ purrr 0.2.5
## ✔ tibble 1.4.2 ✔ dplyr 0.7.6
## ✔ tidyr 0.8.1 ✔ stringr 1.3.1
## ✔ readr 1.1.1 ✔ forcats 0.3.0## ── Conflicts ───────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()