Academics

Libraries announces workshop series on statistical analysis in R and RStudio

Credit: Christopher Blaska / Penn State. All Rights Reserved.

UNIVERSITY PARK, Pa. — Beginning March 13, the research informatics and publishing department at Penn State University Libraries will offer a series of five workshops on statistical analysis in the programming language R. These workshop sessions — Basics of RStudio, Inferential Statistics, ANOVA and Regression Analysis — will provide instruction on using R for statistical analysis and data visualization. 

The workshops are free and open to Penn State graduate students, postdoctoral scholars, faculty and staff. Beginner knowledge of R is recommended for this series. Prior to the start of the workshops, registrants will be given instructions for accessing R.

All workshops will be held virtually via Zoom. Advance registration is required. Register for the workshop series here. Each session builds on the previous one, so registration for the entire series is required. Registration will close March 11.

For additional information, contact research informatics and publishing at repub@psu.edu.

Workshop schedule:

Basics of RStudio Refresher — March 13, 3-5 p.m.

This session will give a basic refresher of core concepts taught in the fall "Research Reproducibility in R" workshop series, such as loading data and packages, and data wrangling.

Exploratory Data Analysis and Making Visualizations — March 20, 3–5 p.m.

This session will introduce how to run exploratory data analysis and make data visualizations using the open-source data visualization package ggplot2.

Introduction to Inferential Statistics — March 27, 3–5 p.m.

This session will introduce inferential statistics including the chi-square, t-test, Kruskal-Wallis and Mann–Whitney test.

ANOVA — April 3, 3–5 p.m.

Participants will have the opportunity to learn how to run ANOVA, ANCOVA and MANOVA for their data analysis.

Regression Analysis — April 10, 3–5 p.m.

Learn regression analysis, when to use contrast and dummy coding and the differences between regression and ANOVA.

Last Updated February 27, 2024