Beyond Multiple Linear Regression

Are you looking to expand your knowledge beyond multiple linear regression in statistics? The textbook “Beyond Multiple Linear Regression: Utilized Generalized Linear Models and Multilevel Models in R” is designed for undergraduate students who have completed a multiple linear regression course. This book helps students develop an expanded modeling toolkit that includes non-standard responses and correlated structures.

While there is no specific mathematical prerequisite, the authors introduce sophisticated topics such as probability theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises in the book utilize real data and research questions, many of which are derived from collaborative research conducted by the authors and their students, as well as student projects.

Each chapter of the book includes a variety of conceptual exercises, guided exercises, and open-ended exercises that use real data. By working through this material, students will enhance their toolkit for statistical modeling and gain a broader understanding of data analysis.

Book Details:

• ISBN-10: 1439885389
• ISBN-13: 978-1439885383
• Edition: 2nd edition
• Author: Susan W. Hardwick

Key Topics Covered in the Book:

• Generalized Linear Models
• Multilevel Models
• Probability Theory
• Zero-inflated Poisson
• Parametric Bootstrapping

If you are interested in advancing your statistical modeling skills and exploring more complex regression models, “Beyond Multiple Linear Regression” is a comprehensive resource that can help you broaden your understanding of statistical analysis.

FAQs

What is the target audience for “Beyond Multiple Linear Regression”?

The book is designed for undergraduate students who have completed a multiple linear regression course and are looking to expand their modeling toolkit.

Are there any mathematical prerequisites for reading this book?

While there is no specific mathematical prerequisite, the book covers sophisticated topics such as probability theory and parametric bootstrapping in an applied manner.

Does the book include real data and research questions?

Yes, the case studies and exercises in the book utilize real data and research questions, providing a practical approach to statistical modeling.

Conclusion

“Beyond Multiple Linear Regression” offers a valuable resource for students and individuals looking to enhance their statistical modeling skills. With a focus on generalized linear models and multilevel models, the book provides a practical and intuitive approach to expanding your toolkit for data analysis. By incorporating real data and research questions, the book offers a hands-on learning experience that can benefit anyone interested in advancing their understanding of statistical modeling.