ISBN-13: 9780470582473

The book “Applied Logistic Regression (3rd Edition)” provides a comprehensive overview of the theory and practical applications of logistic regression in various fields such as statistics, data analysis, and machine learning. The author covers the fundamental concepts of logistic regression, including model building, interpretation of results, and model evaluation.

The book also delves into advanced topics such as multicollinearity, interaction effects, and model selection techniques. Real-world examples and case studies are used throughout the book to illustrate how logistic regression can be applied to solve complex problems in different industries.

Additionally, the book includes step-by-step instructions on how to implement logistic regression models using popular statistical software such as R and SAS. The author also discusses the importance of data preprocessing, model validation, and interpretation of coefficients to ensure the accuracy and reliability of the results.

“Applied Logistic Regression (3rd Edition)” is a valuable resource for researchers, data analysts, and students who want to deepen their understanding of logistic regression and its practical applications in various fields.

This edition retains the full content with the added advantage of portability, allowing readers to easily access and engage with the material from any device, whether in a classroom or during fieldwork.