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Multiple Regression
Multiple Regression
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Readings
  • 1: Intro
  • 2: Fitting Models
  • 3: Inference
  • 4: Model Inference
  • 5: SLR Review
  • 7: MLR Intro
  • 8: MLR Intro 2
  • 9: Parallel / Non-Parallel Slopes
  • 10: Multicollinearity & Nested F
  • 11: Leverage
  • 12: Bootstrap
  • 13: Article Review
  • 14: Data Visualization
  • 15: Transformations
  • 16: Odds & Probability
  • 17: Logistic Intro
  • 18: Logistic Inference
  • 19: Multiple Logistic 1
  • 20: Multiple Logistic 2
  • 21: Logistic Visualization
  • 22: Comparing Models 2
  • 23: Logistic Review

Data Visualization

Read before class on Wednesday, March 11, 2020

Required

  • Healy, K. (2018). Data visualization: a practical introduction. Chapter 6: Work with models. Princeton University Press.

Recommended

  • None

Last updated on February 16, 2020

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SDS 291: Multiple Regression (Spring 2020)
Smith College    Program on Statistical & Data Sciences

Dr. Benjamin Capistrant    bcapistrant@smith.edu

Monday & Wednesday    TBD
Zoom

All content licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Content 2020 Ben Capistrant

A tremendous thanks to Andrew Heiss whose course sites served as the basis for the format and structure of this site. They employ the Academic theme in blogdown and built with Hugo.

View the source at GitHub.

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