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Multiple Regression

Multiple Regression

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Reading details

Reading policy

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

Logistic Regression Review

Read before class on Monday, April 27, 2020

Required

Chapters 9, 10, 11.1-11.2, 11.4

Recommended

Last updated on April 22, 2020

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

Dr. Benjamin Capistrant bcapistrant@smith.edu

Monday & Wednesday TBD
Zoom

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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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