Preliminaries
36-707 Regression Analysis
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Preface
Syllabus
1
Introduction
Preliminaries
2
Causality
3
Matrix and Vector Algebra
Linear Regression
4
Linear Regression Basics
5
Geometric Multiple Regression
6
Linear Models in R
7
Interpreting Regressors
8
The Regressinator
9
Regression Assumptions and Diagnostics
10
Nonlinear Regressors
11
Conducting Inference
Generalized Linear Models
12
Logistic Regression
13
Other Response Distributions
14
Generalized Additive Models
15
The Bootstrap
Interlude: Regression Case Studies
16
Flight Delays
Prediction
17
Prediction Goals and Prediction Errors
18
Estimating Error
19
Penalized Models
20
Kernel Regression
Special Topics
21
Survival Analysis
22
Missing Data
23
Mixed and Hierarchical Models
24
Experimental Design
Statistical Writing
25
Genre Conventions
26
Reporting Results in APA Format
References
Preliminaries
1
Introduction
2
Causality