PRACTICAL REGRESSION MODELING IN R

Unlock the power of regression modeling with Practical Regression Modeling in R, an essential guide for mastering data analysis in R. Designed for students, researchers, and professionals with basic statistical knowledge, this book offers a hands-on approach to building, evaluating, and interpreting regression models. From simple and multiple linear regression to nonlinear and Lasso regression, each chapter blends clear theory with real-world applications, supported by detailed R code.

Dive into practical case studies using datasets like mtcars and Boston Housing, learn to diagnose models with modern techniques, and explore advanced topics through two in-depth appendices on the Levenberg-Marquardt method and matrix algebra. A comprehensive glossary and references make this book a valuable resource for both learning and reference.

With step-by-step R examples, visualizations, and diagnostic tools, Practical Regression Modeling in R equips you to tackle real-world data challenges with confidence. Whether you’re a student starting your first regression project or a professional refining your analytical skills, this book provides the tools to succeed. Start your journey to mastering regression modeling today!