UNIVERSITY PARK, PA. — Beginning March 14, the Research Informatics and Publishing department at Penn State University Libraries will offer a series of five workshops on statistical data analysis and visualization using the programming language R. The series will include a refresher course on the basics of the RStudio integrated development environment, followed by exploratory data analysis and visualizations, inferential statistics, analysis of variance (ANOVA), and regression analysis.
All workshops will be held virtually via Zoom. Participants must register in advance for the entire series using the link provided below. The workshops are free and open to Penn State undergraduate and graduate students, postdoctoral scholars, faculty and staff. Beginner knowledge of R is recommended. Prior to the start of the workshops, registrants will be given instructions on accessing R.
Additional information is provided at the registration link. If you have any questions, contact Research Informatics and Publishing at repub@psu.edu.
Register for this workshop series here. Registration is required and will close March 1.
Spring 2023 Workshop Schedule
R is a programming language that is popular for data exploration, visualization and statistical analysis. This workshop series will focus on using R to run statistical analysis. Each session builds on the previous one, so registration for the entire series is required.
Statistical Analysis in R: Basics of RStudio Refresher — March 14, 2-4 p.m.
This first session will provide a basic refresher of core concepts taught in the fall 2022 Research Reproducibility in R workshop series: loading data and packages, and data wrangling.
Statistical Analysis in R: Exploratory Data Analysis and Making Visualizations — March 21, 2-4 p.m.
This session will introduce how to run exploratory data analysis and make data visualizations using ggplot2.
Statistical Analysis in R: Introduction to Inferential Statistics — March 28, 2-4 p.m.
This session will introduce inferential statistics including chi-square, T-test, Kruskal-Wallis and Mann-Whitney analyses.
Statistical Analysis in R: ANOVA — April 4, 2-4 p.m.
Participants will have the opportunity to learn how to run analysis of variance (ANOVA), analysis of covariance (ANCOVA) and multivariate analysis of variance (MANOVA) for their data analysis.
Statistical Analysis in R: Regression Analysis — April 11, 2-4 p.m.
Learn regression analysis, when to use contrast and dummy coding, and the differences between regression and ANOVA.