My Account
Log in Registration
All
Cart
Highlights
Fiction Books
Non-Fiction Books
Children's Books
Rare Books
Music
DVD & Blu-Ray
Video Games
Category
Wishlists
Cart
All
Free Shipping in Australia
Trustpilot
Proud to be B-Corp

Linear Regression Models John P. Hoffmann

Linear Regression Models By John P. Hoffmann

Linear Regression Models by John P. Hoffmann

Reviews:
$161.69
Condition - New
Only 2 left
New

Summary

This book includes chapters on specifying the correct linear regression model, adjusting for measurement error, understanding the effects of influential observations, and using multilevel data.

Linear Regression Models Summary

Linear Regression Models: Applications in R by John P. Hoffmann

*Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied.
*Uses numerous graphs in R to illustrate the model's results, assumptions, and other features.
*Does not assume a background in calculus or linear algebra; rather, an introductory statistics course and familiarity with elementary algebra are sufficient.
*Provides many examples using real world datasets relevant to various academic disciplines.
*Fully integrates the R software environment in its numerous examples.

About John P. Hoffmann

John P. Hoffmann is a professor of sociology at Brigham Young University. He holds a PhD in Criminology from the State University of New York at Albany and a Masters of Public Health (MPH) from Emory University. He has worked at the U.S. Centers for Disease Control and Prevention (CDC) and the National Opinion Research Center (NORC) of the University of Chicago; and taught at Hokkaido University and the University of South Carolina. Hoffmann is the author of more than 100 journal articles and book chapters and 10 books on applied statistics, criminology, and the sociology of religion.

Table of Contents

1. Introduction
2. Review of Elementary Statistical Concepts
3. Simple Linear Regression Models
4. Multiple Linear Regression Models
5. The ANOVA Table and Goodness-of-Fit Statistics
6. Comparing Linear Regression Models
7. Indicator Variables in Linear Regression Models
8. Independence
9. Homoscedasticity
10. Collinearity and Multicollinearity
11. Normality, Linearity, and Interaction Effects
12. Model Specification
13. Measurement Errors
14. Influential Observations: Leverage Points and Outliers
15. Multilevel Linear Regression Models
16. A Brief Introduction to Logistic Regression
17. Conclusions
Appendix A: Data Management
Appendix B: Using Simulations to Examine Assumptions of Linear Regression Models
Appendix C: Formulas
Appendix C: User-Written R Packages Employed in Examples

Additional information

NLS9780367753665
9780367753665
0367753669
Linear Regression Models: Applications in R by John P. Hoffmann
John P. Hoffmann
Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
New
Paperback
Taylor & Francis Ltd
2021-09-13
420
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

Customer Reviews - Linear Regression Models