| Date |
Slides |
Topics |
Data |
| Jan. 24 |
Intro to R |
Setting working directory and RProjects; RScripts and RMarkdown files; basic functions in R |
|
| Jan. 31/Feb. 7 |
Intro to R |
Types of data in R; summary statistics; visual summaries of data; Tidyverse; missing data |
Intro Survey
|
| Feb. 14/21 |
Summarizing Data |
Summarizing relationships between 2+ variables; logical conditions |
NOMINATE
*
|
| Feb. 21/28 |
Statistical Relationships |
Correlation coefficients, Law of Large Numbers, Central Limit Theorem, Hypothesis Testing |
|
| Mar. 7 |
Sources of Error and Bias in Research |
Sources of Error and Bias in Research: Measurement Error, Sampling Error, Nonresponse Bias, Confounding/Omitted Variables Bias |
|
| Mar. 28 |
Linear Regression |
OLS, Challenges of Causal Inference with Observational Data, Confounding Variables |
Experiment Data
Confounding Variable Data
Regression Data
|
| April 4/11 |
Data Analysis (Worked Example) |
Theory/Hypotheses, Summary Statistics, Research Design and Analysis (Regression) |
2020 Campaign Finance Data
**
|
| April 25 |
Response Bias and Qualitative Research Designs |
Addressing Social Desirability Bias (List Experiments); choosing case studies; course summary |
CES Self-Reported Turnout Data
True Turnout Data
***
|
