Albert Y. Kim and Adriana Escobedo-Land

Data and code for OkCupid Profile Data for Introductory Statistics and Data Science Courses, Journal of Statistics Education July 2015, Volume 23, Number 2. The original manuscript was subsequently revised in 2021.

• JSE_revised.Rnw: .Rnw source document to recreate JSE_revised.pdf using knitr. In RStudio, go to “Tools” -> “Project Options” -> “Sweave” -> “Weave Rnw files using:” and select knitr.
• JSE_revised.pdf: PDF of document
• JSE_revised.bib: bibliography file
• JSE_revised.R: R code used in document
• okcupid_codebook_revised.txt: codebook for all variables
• profiles_revised.csv.zip: CSV file of revised profile data (unzip this first)
• essays_revised_and_shuffled.zip: CSV file of shuffled essay data (unzip this first)

• Revisions in 2021:
  • Removed the exact date the data was collected.
  • Shuffled/randomized the order of the rows of the essay data, thereby decoupling the essay data from the profiles data.
  • Removed URL’s in the essay data that involved the following domains: facebook.com, instagram.com, twitter.com, pinterest.com, and flickr.com.
  • Added random noise to age variable in the profiles data.
  • Removed the following variables from the profiles data: location, last online
• Original version from 2015:
  • Permission to use this data set was explicitly granted by OkCupid.
  • Usernames are not included.

A mosaicplot of the cross-classification of the 59946 users’ selected sex and sexual orientation:

Linear regression (in red) and logistic regression (in blue) compared. Note both the x-axis (height) and y-axis (is female: 1 if user is female, 0 if user is male) have random jitter added to better visualize the number of points involved for each (height x sex) pair.

Fitted probabilities p-hat of each user being female along witha decision threshold (in red) used to predict if user is female or not.