Linear Regression
A tutorial introduction to the mathematics of regression analysis
About this book
Linear regression is the workhorse of data analysis. It is the first step, and often the only step, in fitting a simple model to data. This brief book explains the essential mathematics required to understand and apply regression analysis.
The tutorial style of writing, accompanied by over 30 diagrams, offers a visually intuitive account of linear regression, including a brief overview of nonlinear and Bayesian regression. Hands-on experience is provided in the form of numerical examples, implemented online with Python and MATLAB code. Supported by a comprehensive glossary and tutorial appendices, this book is an ideal introduction to regression analysis.
The books below contain identical text, but Linear Regression with MatLab and Linear Regression with Python include code at the end of chapters (link to code below) which reproduces key figures and numerical results.
Download Chapter 1 (PDF, 1.9MB)
Linear Regression
A tutorial introduction to the mathematics of regression analysis
ISBN: 9780956372895
Table of contents (PDF, 148KB)
Available from:
Linear Regression with Matlab
A tutorial introduction to the mathematics of regression analysis
ISBN: 978-0993367908
Table of contents (PDF, 149KB)
Available from:
Linear Regression with Python
A tutorial introduction to the mathematics of regression analysis
ISBN: 978-0993367939
Table of contents (PDF, 148KB)
Available from: