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Statistical Modeling in R

Description of Workshop

This workshop is part of the Summer Data Science Workshops hosted by Research Computing Services at Northwestern University (2019).

The purpose of the workshop is to introduce students in how to conduct statistical modeling with linear models, the most used generalized linear models, hierarchical linear models and survival analysis in R. This workshop will also include some exploratory data analysis and diagnostics.

Students are expected to have knowledge of R and regression analysis.


This workshop requires packages: pastecs, lm.beta, lmtest, foreign, lattice, lme4, nlme, survival, dplyr, ggfortify, survminer, rms, MASS, pscl.


The presentations are available in the slides directory.

Downloading Files

Recommended: Entire directory

You can download all of the files by clicking the green button ("Clone or download") above and choosing "Download ZIP."

Individual Files

If you download files from the links above, you have to click through to the RAW version of the R markdown files and download that. If you download directly from the links above, the files won't open because they are web pages, not the raw files.

Downloading Exercises

To download just the exercise files, right-click on the links below, and choose Save Link As (or the similar option in your browser). Make sure to choose All file types as the content type (or .ipynb if available), and remove any .txt or similar extensions from the file when you save it. The files should be *.ipynb files, with no additional file type extensions.

Exercises WITHOUT Answers

Exercises WITH Answers


See Resources for a listing of general Python resources, tutorials, and reference materials. Links below relate specifically to material covered in this workshop.

Linear models in R: this is brief dicussion of linear models in R. There is also another tab on GLMs.

Statistical Formula Notation in R: notes on regression notation in R

GLMs blog series in R: this a link to the first of a seven part series on GLMs in R.

Log-linear model in R: Really accessible discussion on log-linear models.

Tutorial on Survival Analysis: pretty good discussion of comparsion of survival techniques.

Survival Analysis Cheat Sheet: common models and steps

Hierarchical models: modules on hierarchical linear models (extension module 4 is on R)

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