Regression Analysis with R

What this book covers

Chapter 1, Getting Started with Regression, teaches by example why regression is useful for data science and how to quickly set up R for data science. We provide an overview of the packages used throughout the book.

 

Chapter 2, Basic Concepts – Simple Linear Regression, introduces regression with the simplest algorithm: simple linear regression. The chapter first describes a regression problem and where to fit a regressor, and then gives some intuitions underneath the math formulation.

Chapter 3, More Than Just One Predictor – MLR, shows how simple linear regression will be extended to extract predictive information from more than a feature. The stochastic gradient descent technique, explained in the previous chapter, ...