Regression and inference

Readings

• Chapter 2 in Mastering ’Metrics Joshua D. Angrist and Jörn-Steffen Pischke, Mastering ’Metrics: The Path from Cause to Effect (Princeton, NJ: Princeton University Press, 2015).
• “Properties of regression” in Causal Inference: The Mixtape Scott Cunningham, Causal Inference: The Mixtape, 2018, https://www.scunning.com/mixtape.html.

Recommended readings

Look through your notes on regression from your last stats class. Also, you can skim through these resources:

• 6.1–6.4 in ModernDive Chester Ismay and Albert Y. Kim, ModernDive: An Introduction to Statistical and Data Sciences via R, 2018, https://moderndive.com/.
• 7.1–7.4 in ModernDive Ismay and Kim, ModernDive.
• 7.1–7.3 in OpenIntro Statistics David M. Diez, Christopher D. Barr, and Mine Çetinkaya-Rundel, OpenIntro Statistics, 3rd ed., 2017, https://www.openintro.org/stat/textbook.php?stat_book=os.
• 8.1 in OpenIntro Statistics Diez, Barr, and Çetinkaya-Rundel, OpenIntro Statistics.

We’ll review all this regression stuff in the videos, so don’t panic if this all looks terrifying! Also, take advantage of the videos that accompany the OpenIntro chapters. And also, the OpenIntro chapters are heavier on the math—don’t worry if you don’t understand everything.

Slides

The slides for today’s lesson are available online as an HTML file. Use the buttons below to open the slides either as an interactive website or as a static PDF (for printing or storing for later). You can also click in the slides below and navigate through them with your left and right arrow keys.

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• Introduction
• Drawing lines
• Lines, Greek, and regression
• Null worlds and statistical significance

Videos

Videos for each section of the lecture are available at this YouTube playlist.

• Introduction
• Drawing lines
• Lines, Greek, and regression
• Null worlds and statistical significance

You can also watch the playlist (and skip around to different sections) here: