Applied Regression Modeling

Practical regression, written for real classroom use

Applied Regression Modeling brings regression analysis down to the level where it is most useful: interpreting data, choosing sensible models, and understanding what the output actually means. This third edition is built around applied statistics rather than calculus-heavy derivations, which makes it a strong fit for students and professionals who want a clear path into regression without getting buried in theory.

The book moves steadily from statistical foundations to simple linear regression, then into multiple linear regression and model building. Along the way, it covers transformations, interactions, qualitative predictors, influential points, regression pitfalls, model selection, and graphical interpretation. The structure is especially helpful for readers who want to see how the pieces of regression fit together instead of treating each topic as an isolated technique.

What the book emphasizes

• Core statistical ideas that support regression work
• Model fitting, checking, and interpretation
• Practical diagnostics and common modeling problems
• Building better regression models with transformations and predictor types
• Applied examples supported by homework problems and real datasets

Designed for applied learning

The text is aimed at undergraduate and graduate statistics courses where regression is the main subject, but it also suits MBA and other applied professional settings. The tone of the book, as reflected in the front matter, favors software-based analysis, clarity of interpretation, and a minimum of mathematical overhead. That makes it a useful choice for readers who need to work with regression models in practice, not just study them abstractly.

Extra support for study and teaching

The third edition is supported by companion materials that include datasets, software guidance, case studies, and other learning resources. Those additions make it easier to move from reading about regression to actually using it on real problems.

If you want a focused, classroom-tested introduction to regression that stays practical from start to finish, this edition offers exactly that balance of structure, clarity, and application.