Resources
Lectures
We post the worksheet, its answer key, and the slides for each lecture here after class, with the newest lecture at the top. There is no way to submit a worksheet after class, so the copy here is for review.
- Lecture 7 (Wed Oct 14): z-scores and the normal distribution — worksheet · answer key · slides
- Lecture 6 (Mon Oct 12): Quantifying error — worksheet · answer key · slides
- Lecture 5 (Wed Oct 7): The mean as a model — worksheet · answer key · slides
- Lecture 4 (Mon Oct 5): Explaining variation — worksheet · answer key · slides
- Lecture 3 (Wed Sep 30): Distributions & histograms — worksheet · answer key · slides
- Lecture 2 (Mon Sep 28): Sampling & measurement — worksheet · answer key · slides
- Lecture 1 (Wed Sep 23): What is statistics? — worksheet · answer key · slides
Tutorials
We post the handout for each Friday tutorial here once that day’s sessions are over, along with an answer key.
- Tutorial 3 (Fri Oct 9): The Vault of Fallen Labels — handout · answer key
- Tutorial 2 (Fri Oct 2): The Sleep Lab Incident — handout · answer key
- Tutorial 1 (Fri Sep 25): Orientation Day at Strangeford — handout · answer key
Other resources
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CourseKata: Statistics and Data Science — our textbook. Access it through the Modules on Canvas.
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Setting up your laptop before your first discussion section in Week 1 (the install clinic): download and install R first, then RStudio Desktop. Both are free. The full instructions and the package-install script are on the Project page.