| Date |
Slides |
Topics |
Data |
| May 22 |
Intro to R |
Setting working directory and RProjects; RScripts and RMarkdown files; basic functions in R |
|
| May 24 |
Intro to R |
Basic functions in R; types of data in R; reading data into R |
2020 Campaign Finance Data
*
|
| May 31 |
Types of Data in R |
Types of Data in R; conditional logic |
|
| June 2 |
Intro to dplyr |
Overview of key functions in dplyr (filter, select, mutate, and joins) |
|
| June 5 |
Intro to ggplot |
Plotting in ggplot; creating visual summaries of 1, 2, 3, and more variables |
|
| June 7 |
Intro to t-tests |
Law of Large Numbers; Central Limit Theorem; Confidence Intervals; Hypothesis Testing |
|
| June 12 |
Tables, Chi-Squared Tests, and Correlation Coefficients |
Making tables in R; applying survey weights; Chi-Squared Tests; Correlations |
CES 2020 Example
**
|
| June 14 |
Intro to Regression |
Causality; Confounding variables/Omitted Variables Bias; Bivariate Regression; Multivariate Regression; Making nice regression tables |
Regression Data
Regression Data (with Confounder)
***
|
| June 21 |
Dummy Variables, Dot-and-Whisker Plots, and Predictions |
Dummy/indicator variables in regression; creating visual summaries of regression models; making predictions from regression models |
|
| June 23 |
Interaction Effects and Marginal Effects |
Understanding and interpreting interaction effects; estimating and visualizing interactions; estimating marginal effects in R |
|
