STA 210: Regression Analysis

Learn approaches for analyzing multivariate data sets, emphasizing analysis of variance, linear regression, and logistic regression. Learn techniques for checking the appropriateness of proposed models, such as residual analyses and case influence diagnostics, and techniques for selecting models. Gain experience dealing with the challenges that arise in practice through assignments that utilize real-world data. This class emphasizes data analysis over mathematical theory.


Course info

Lectures

  Gross Hall 103      Mon and Wed 3:05p - 4:20p

Labs

Lab 01      Soc Psych 127      Thu 3:05p - 4:20p

Lab 02      Soc Sci 119           Thu 4:40p - 5:55p

Teaching team and office hours

Instructor Prof. Maria Tackett   Tue 3p - 4:30p Old Chem 118B
TAs Cody Coombs   Tue 1p - 3p Old Chem 203B
Matty Pahren   Tue 10a - 12p Old Chem 203B
Ethan Shen   Thu 6p - 8p Old Chem 203B
Steven Winter   Wed 12p - 2p Old Chem 203B
Tong Wu   Fri 11:30a - 1:30p Old Chem 203B
Evan Wyse   Mon 12:30p - 2:30p Old Chem 203B

Textbooks

Handbook of Regression Analsyis James, Witten, Hastie, Tibshirani Springer, 1st edition, 2013 Freely available on Sakai
R for Data Science Chatterjee, Simonoff Wiley, 1st edition, 2013 Freely available online

Materials

You should bring a fully-charged laptop or comparable device to every lecture and lab session.