Praise for the Fourth Edition:

"This book is . . . an excellent source of examples for
regression analysis. It has been and still is readily readable and
understandable."

?Journal of the American Statistical
Association Regression analysis is a conceptually simple
method for investigating relationships among variables. Carrying
out a successful application of regression analysis, however,
requires a balance of theoretical results, empirical rules, and
subjective judgment. Regression Analysis by Example, Fifth
Edition has been expanded and thoroughly updated to reflect
recent advances in the field. The emphasis continues to be on
exploratory data analysis rather than statistical theory. The book
offers in-depth treatment of regression diagnostics,
transformation, multicollinearity, logistic regression, and robust
regression.

The book now includes a new chapter on the detection and
correction of multicollinearity, while also showcasing the use of
the discussed methods on newly added data sets from the fields of
engineering, medicine, and business. The Fifth Edition also
explores additional topics, including:

• Surrogate ridge regression


• Fitting nonlinear models


• Errors in variables


• ANOVA for designed experiments

Methods of regression analysis are clearly demonstrated, and
examples containing the types of irregularities commonly
encountered in the real world are provided. Each example isolates
one or two techniques and features detailed discussions, the
required assumptions, and the evaluated success of each technique.
Additionally, methods described throughout the book can be carried
out with most of the currently available statistical software
packages, such as the software package R.

Regression Analysis by Example, Fifth Edition is suitable
for anyone with an understanding of elementary statistics.