Open Stats Lab (OSL) is a website created by Kevin P. McIntyre, Ph.D., that uses open data sets from articles published in Psychological Science to help teach introductory statistics. For each OSL lab, I've identified studies with open data badges, and then prepared activities that guide students through the analyses needed to reproduce the results reported in the original articles.


Psychology has experienced a major transition with respect to how we conduct and report statistical analyses.  Following the exposure of fraudulent research (see Bhattacharjee, 2013) and the failure to replicate several published studies (Klein et al., 2014), many scientists have called for researchers to publish their data sets for use and analysis by other researchers (Asendorpf et al., 2013).  

Many journals, including Psychological Science (Eich, 2014; Lindsay, 2015), have encouraged researchers to adopt open data practices as a way to increase both the reliability of and confidence in psychological research.  An important next step in advancing open science in psychology is to incorporate these principles into undergraduate-level statistics and methods courses.  OSL seeks to contribute to this effort by creating a repository of open data sets, and activities based on those data sets, for use in statistics instruction.

OSL Lab-Based Approach

OSL is primarily a resource for the teaching (and learning) of statistics. Although many statistics textbooks come with supplemental data sets to help train students in data analysis, these data sets often lack the richness and complexity of "real" data.  In addition, most of these supplemental data sets are boring and ask students to analyze problems that they don't care about.  In contrast, OSL labs use the actual data sets from published research and allow students to reproduce the latest findings in psychological science.  

Each OSL lab is comprised of three components: a published article, a data set, and an activity for students.  The lab activities guide students through the reproduction of the results reported in one of the studies from the published paper.  In addition, some of the activities also focus on issues related to data analysis, such as computing new variables.  

Using OSL with Different Software Packages

OSL provides activities to help students reproduce the results of published research.  Each of the activities is written for data analysis using SPSS.  OSL is not a guide to using SPSS, however.  Students should have a working knowledge of SPSS and its basic functions (recoding variables, computing variables, selecting cases, etc.) in order to get the most out of OSL activities.  In addition, many of the activities were written for R by Dr. Matthew Ling of Deakin University. You can access the R scripts via the buttons on each page. To run the analyses in R (or other software packages), you can access plain text data sets via the  buttons.


OSL was created with the help of a grant from the Association for Psychological Science, Fund for Teaching and Public Understanding of Psychological Science. I would also like to thank Natalie Perez (Communication + New Media, '17, Trinity University) for creating the website and custom graphics, Matthew Ling for writing the R scripts, and Sage Publications for providing users of OSL with free access to each of the Psych Science articles.