Week 5 - Inference with One Regressor
Overview
As we carry on into the wonderful world of statistical inference, expect flashbacks of our statistics review. That’s what the review was for! It’s all coming together 😌.
Reading Guide
Chapter 5: Hypothesis Tests and Confidence Intervals
SW 5.1 Testing Hypotheses About One of the Regression Coefficients
This is very important stuff. Again, don’t worry about calculating the variance of a beta coefficient by hand. However, note how similar this is to our hypothesis testing in Chapter 3!
SW 5.2 Confidence intervals for a regression coefficient
SW 5.3 Regression when X is a binary variable
We are going to use this ALL THE TIME.
SW 5.4 Heteroskedasticity and homoskedasticity
Drop “heteroskedasticity” into any conversation and you’re sure to delight. Just one more benefit of EC200. The examples and implications of heteroskedasticity are important.
And, now you’ll know to add , robust to all your Stata regressions. (Quick, someone tell Nate Silver!)
SW 5.5 Theoretical foundations of OLS
Know the Gauss-Markov theorem and related assumptions. Skip “regression estimators other than OLS.” The appendix contains a proof of the Gauss-Markov theorm, but we will not cover that.
SW 5.6 Skip this section!
SW 5.7 Conclusion
For the good times.
Other resources
- EGAP: 10 things to know about hypothesis testing
- EGAP: 10 things to know about statistical power - gets a bit deeper than we go, but accessible and handy!