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Resources |
The R Overview page provides background on installing R and RStudio and using markdown to create data-driven documents.
For a refresher on core stats concepts that serve as pre-requisites to this course, visit the stats review page.
- Regression Review Assessment [ pdf ]
- Common Statistics Notation [ pdf ]
- Anscomb's Quartet [ pdf ]
- Omitted Variable Bias Calculation
- Seven Sins of Regression [ pdf ]
- Marginal Effects in Quadratic Model [ pdf ]
- Dummy Variables with Interactions [ pdf ]
- A Taxonomy of Control Variables [ pdf ]
The following provide useful tutorials that offer R syntax for common regression techniques.
- UC Business Analytics [ link ]
- By Manny Gimond [ link ]
- Listen Data [ link ]
- Machine Learning Plus [ link ]
- Learning regression in R using Moneyball models [ link ]
- regression animations [ link ]
- much nicer but more complex animations [ link ]
- Mathematics in R Markdown [ link ]
- plm: panel linear models
- coefplot: create coefficient plots
- dplyr: data wrangling
- stargazer: nice regression tables
- pander: formatting tables
- xtable: formatting tables
- Intro to Stats review in R [ teacup giraffe textbook ]
- OpenIntro Statistics
- CH-08 Intro to Regression
- Discovering Statistics in R
- Comprehensive guide to using R for a variety of statistical models
- Real Stats: Using Econometrics for Political Science and Public Policy
- Regression models from a causal inference and evaluation perspective
- OpenStax free Introductory Statistics textbook
- Good review of intro statistics:
- Chapter 1 – Sampling Data
- Chapter 2 – Descriptive Statistics
- Chapter 8 – Confidence Intervals
- Chapter 9 – Hypothesis Testing with One Sample
- Chapter 10 – Hypothesis Testing with Two Samples
- Chapter 12 – Linear Regression and Correlation