College of Graduate Studies

Join us on an exciting journey into the world of data with our introductory workshops! This session will address importing Excel and comma separated value files into R for analysis.

Join us on an exciting journey into the world of data with our introductory workshops! This session will introduce participants to common tasks of initial data exploration.

Explore the variety of ways that data can be filtered and subset in R. Working with data frames and vectors, data frames, and lists, participants will learn the nuances of extracting portions of a larger data set for analysis.

This session will revisit the vector underpinnings of R, introduce the apply() family of functions for iterating, or looping, over objects, and introduce for loops for those instances when no pre-existing solution exists.

This session will introduce conditionals in R, addressing those times when, for example, if something is true x needs to happen, otherwise y needs to happen. Participants will be introduced to pre-existing if / else constructs, as well as how to construct conditional statements from scratch.

Unlock the secrets of crafting impactful literature reviews in this interactive online workshop for graduate students. Discover how to synthesize existing research succinctly while maintaining your own critical perspective and voice.

This workshop will demystify ANOVAs by framing them in the context of linear models with multiple predictors (i.e., multiple linear regression). The session will also introduce attendees to Directed Acyclical Graphs (DAGs) and demonstrate how to use them to infer causality in one’s model.

By the end of this session participants should be able to fit linear models with more than one predictor, check for collinearity between predictors, and interpret linear models using DAGs.