Stone J. Linear Regression With Python: A Tutorial Introduction to the Mathematics of Regression Analysis

Sebtel Press, 2022. - 139 p. - ISBN 191627918X.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, included as Python code at the end of each chapter, and implemented online as Python and MatLAB code. Supported by a comprehensive glossary and tutorial appendices, this book provides an ideal introduction to regression analysis.Preface.
What is Linear Regression?
Finding the Best Fitting Line.
How Good is the Best Fitting Line?
Statistical Significance: Means.
Statistical Significance: Regression.
Maximum Likelihood Estimation.
Multivariate Regression.
Weighted Linear Regression.
Nonlinear Regression.
Bayesian Regression: A Summary.
A Glossary.
B Mathematical Symbols.
C A Vector and Matrix Tutorial.
D Setting Means to Zero.
E Key Equations.
Index.True PDF