1 Statistical Learning as a Regression Problem
1.1 Getting Started
1.2 Setting the Regression Context
1.3 Revisiting the Ubiquitous Linear Regression Model
1.3.1 Problems in Practice
1.4 Working with Statistical Models that are Wrong
1.4.1 An Alternative Approach to Regression
1.4.2 More on Statistical Inference with Wrong Models
1.4.3 Introduction to Sandwich Standard Errors
1.4.4 Introduction to Conformal Inference
1.4.5 Introduction to the Nonparametric Bootstrap
1.4.6 Wrong Regression Models with Binary Response Variables
1.5 The Transition to Statistical Learning
1.5.1 Models Versus Algorithms
1.6 Some Initial Concepts
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