Linear regression
Linear Statistical Models
Preface
Linear regression
1
Basic regression
2
Linear regression with a single predictor
3
Fitting linear regression
4
Prediction and Bayesian inference
5
Linear regression with multiple predictors
6
Model diagnostics and evaluation
7
Logarithmic transformations
8
Comparing regression models
Generalized linear models
9
Logistic regression
10
Logistic regression with multiple predictors
11
Diagnostics of logistic regression models
12
Generalized linear models
13
Poststratification: regression with non-representative sample
Causal inference
14
Basics of causal inference
15
Causal inference with regression
16
Causal inference with observational data
17
Subclassification and propensity score matching
18
Instrumental variables
19
Regression discontinuity
20
Difference-in-differences
21
Panel data
22
Synthetic control
Conformal prediction
23
Full & split conformal prediction
24
Jackknife+, CV+ and Quantile regression
25
Conformal prediction for classification
Linear regression
In the first part, we will study linear regression.
Preface
1
Basic regression