These materials are annotated lab assignments I developed for teaching statistical programming in Stata (Version 13 or above).
These lessons were geared toward PhD students in Sociology and other fields taking SOC385L (Linear Models / Multiple Regression) a required second semester course in graduate statistics.
I served as a Teaching Assistant for this course three times, in Spring 2012 and Spring 2014 with Professor Pamela Paxton, and in Spring 2016 with Professor Daniel Powers.
These materials formed the basis for a standard set of lab instruction materials used by all TAs in this course for the past several years.
These materials follow a progression of increasingly advanced topics including:
- Coding and data cleaning
- Measurement and variable creation
- Simple and Multiple OLS Regression
- OLS Assumption Violations and Diagnostics
- Outliers and Influential Cases
- Heteroskedasticity
- Multicollinearity and serial autocorrelation
- Fixed and Random Effects Models for Panel Data
- Logit and Probit Models for Binary Outcomes
- Simple Simultaneous Equation Models
- 2 and 3 stage least squares
- Advanced Tips and Tricks