Linear regression

Topics

• 9/1 Introduction
• 9/8 Coding toolkit (R, RStudio, Rmd, GitHub desktop, create GitHub website)
• 9/13 Exploratory data analysis (EDA)
• 9/15 Exploratory data analysis + how to submit an assignment on your website
• 9/20 How to characterize a variable’s distribution
• 9/22 Comparing variables
• 9/27 Linear regression
• 9/29 Exam 1 review
• 10/6 Data ethics
• 10/11 Data ethics, continued
• 10/13 Understanding randomness
• 10/18 Simple linear regression in R
• 10/20 Hypothesis testing (t-test)
• 10/25 Data transformations for linear regression
• 10/27 Exam 2 review
• 11/3 ANOVA (and why this is the same as a linear regression)
• 11/8 Interpreting p-values, confidence intervals, credible intervals
• 11/10 Introduction to causal inference
• 11/15 The probability of causation
• 11/17 Experiments
• 11/22 Causal analysis of risk assessment in criminal sentencing
• 11/29 Difference-in-differences
• 12/1 Regression discontinuity, instrumental variables