Books like Data analysis and regression by Frederick Mosteller

The Elements of Statistical Learning explains key statistical methods that underlie modern machine learning, data mining, and bioinformatics, covering supervised and unsupervised learning techniques such as classification trees, neural networks, and support vector machines.

Applied Linear Statistical Models – a comprehensive textbook by John Neter that covers linear models, regression analysis, analysis of variance, and experimental design for statisticians and researchers.

The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.

An Introduction to Statistical Learning offers a practitioner‑friendly guide to modern statistical learning methods, including linear regression, classification, resampling, shrinkage, tree‑based models, SVMs, and clustering, with R tutorials and real‑world examples.

A practical guide for applying regression techniques to real data, illustrating common irregularities, assumptions, and evaluation steps with clear examples that can be run in standard statistical software.