This repository contains the lab session material for the first course of the quantitative method series of Duke Political Science Ph.D. Program: Probability and Regressionbility (PS630).

R Quick Guide: R, RMarkdown installation and resources

Lab 1: R Basics: R base function, importing data; manually compute summary stastics

Lab 2: dplyr & T-test : clean and manage data using dplyr, magrittr, etc.; manually perform T-test

Lab 3: ggplot & OLS : data visualization using using ggplot, manually perform OLS, export regression table using stargazer

Lab 4: Hypothesis tests, Heteroskedasticity, Regression Diagnostics, Non-linearity : using R to conduct hypothesis tests mannually, run regression diagnostics using plot(), logged transformation, and quadratic regression.

Lab 5: Matrix & Intro to Multivariate Regression: matrix, multivariate regression, omitted variable bias, multicollinearity

Lab 6: Heteroskedasticity: test for heteroskedasticity (visualization, rvf, BP, and White test),heteroskedasticity-robust standard error, Weighted Least Squares & Feasible Generalizable Least Squares

Lab 7: Goodness of Fit: functional programming in R, goodness of fit, joint significance tests

Lab 8: Dummy Variable & Interaction: dummy variable & categortical variable, interaction effect, marginal Effect

Lab 9: Difference-in-Differences: model setup, assumptions, generalized DiDs

Lab 10: Sampling: power calculator, sampling methods

Some materials are from Introduction to Econometrics with R by Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer https://www.econometrics-with-r.org/.