Basic Statistical Analysis in R (In Person) 

Workshop Location: Upson 225

This is the second workshop in the three-part Essentials of R for Statistical Analysis workshop series. This series teaches the essential concepts and skills participants need to work with and analyze their own datasets in R. It is designed for people with little or no experience with programming or statistics. 

In this workshop, participants will learn how to conduct, interpret, and evaluate commonly used statistical analyses in R. The session introduces descriptive statistics and foundational inferential methods, including t-tests, chi-squared tests, correlation analysis, simple linear regression, and one-way ANOVA. Participants will also learn how to assess model assumptions and select methods appropriate for their data and research questions. 

Before the workshop, please install R and RStudio by following the instructions at cscu.cornell.edu/installr. 

Topics include: 

• Descriptive statistics 

• T-tests 

• Chi-squared tests 

• Simple linear regression 

• Correlation analysis 

• One-way ANOVA 

• Model assumptions 

Instructor: Matt Thomas, Statistical Consultant, Cornell Statistical Consulting Unit (CSCU)