2.7 — Inference for Regression — Readings

Note these readings are the same as last class, 2.6!

Strongly Recommended

• [Ch. 4] in Michael A BaileyReal Econometrics (New York: Oxford University Press, 2017).
  
  
• Ch. 10 (optionally 8-9) in Modern Dive
• Last Week Tonight with John Oliver: Scientific Studies
• Visualizing Probability and Inference

Bailey teaches inferential statistics in the classical way (with reference to theoretical \(Z\) and \(t\) distributions, and \(Z\) and \(t\) tests). This is all valid. Again, you may wish to brush up with Khan AcademyFrom sampling distributions through significance tests, for this. Though the whole class is helpful!

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The latter “book” (also free online, like R4DS) uses the infer package to run simulations for inferential statistics. Chapter 10 is focused on regression (but I also recommend the chapters leading up to it, which are on inferential statistics broadly, using this method).

Also be sure to watch the excellent and hilarious discussion of the limits and misuses of scientific studies and statistical significance \((p\)-values) in the Last Week Tonight clip.

The final link is a great website for visualizing basic statistic concepts like probability, distributions, confidence intervals, hypothesis tests, central limit theorem, and regression.