George C. Gordon Library

Join us for a week-long series of data and open science (virtual) workshops!

Register at :


Monday August 9th, 10AM – 12 PM EST

Led By: Dr. Adam Sales

Title: A Primer on the P-Value Controversy, and Replicable Research

Description: Over the past decade or so, researchers in nearly every field of quantitative research have increasingly questioned (or attacked!) the use of p-values and hypothesis tests in statistics. At the same time, a number of fields have entered "replication crises" as notable studies of the past fail to replicate. We will discuss several of the most important problems with p-values that impact research replicability--issues of interpretation, multiple comparisons, post-selection inference, and effect-size inflation--and some proposed solutions.


Tuesday August 10th, 1PM – 4PM EST

Led By: Ethan Prihar

Title: A Brief Introduction to Python for Data Analysis

Description: This class will start from the basics, installing python and packages like numpy and pandas, getting a Jupyter Notebook running, etc. After that we will process an example data set together, do some basic statistics, data cleansing, and plotting. Ideally, after this class, you'll be able to refer to the Juypter Notebook you made during the class as a starting point for data analysis you do in the future.


Wednesday, August 11th,  2-3:30 PM EST

Led By: Dr. Stacy Shaw

Title: An Introduction to Open Science Practices

Description: Open Science practices are techniques and activities that can help make your research more open, transparent, and reproducible. In this talk, you will learn about open science, and the types of practices (such as preregistration and open data sharing) that researchers have been increasingly adopting to make their science more open. The focus of this talk will be the benefits of engaging in these open science practices, how to start adopting these practices, and some work arounds to common challenges researchers face.


Thursday August 12th, 2:00-3:30 PM EST

Led By: Dr. Stacy Shaw

Title: Basic Statistical Analyses using R

Description: This workshop will provide a general introduction to data analysis using R. Students will learn how to import their data, change variable type, and make histograms, bar plots, and box-plots to explore their data. They will also learn how to run descriptive statistics, and conduct t-tests, ANOVAs, regressions, and binomial regressions. Before attending this class, students should download R and RStudio and update their software as necessary if they wish to follow along.


Friday August 13th 11:00AM-12:30PM EST

Led By: Hannah Smith

Title: Basic Statistical Analysis Using JASP: The free, friendly and flexible software

Description: JASP is an open-source software that allows you to run basic frequentist or bayesian statistical analysis from descriptive statistics to factor analysis to ANOVAs. The friendly drag and drop user interface is inviting to users of all statistics backgrounds and the easily sharable output format allows users to share results easily. This workshop will cover how to run and export descriptive statistics, correlations, t-tests, and ANOVAs in JASP as well as how to make graphs and tables that can be placed directly into an APA text or project.



Sponsored by the Gordon Library