
Multiple Regression
A Practical Introduction
SAGE Publications Inc (Publisher)
1st Edition
Published on 2. March 2021
Book
Paperback/Softback
280 pages
978-1-5443-3970-2 (ISBN)
Description
Multiple Regression: A Practical Introduction is a text for an advanced undergraduate or beginning graduate course in statistics for social science and related fields. Also, students preparing for more advanced courses can self-study the text to refresh and solidify their statistical background. Drawing on decades of teaching this material, the authors present the ideas in an approachable and nontechnical manner, with no expectation that readers have more than a standard introductory statistics course as background. Multiple regression asks how a dependent variable is related to, or predicted by, a set of independent variables. The book includes many interesting example analyses and interpretations, along with exercises. Each dataset used for the examples and exercises is small enough for readers to easily grasp the entire dataset and its analysis with respect to the specific statistical techniques covered.
A website for the book includes SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book. Solutions to two of the end-of-chapter exercise types are also available for students to practice. The instructor side of the site contains editable PowerPoint slides, other solutions, and a test bank.
A website for the book includes SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book. Solutions to two of the end-of-chapter exercise types are also available for students to practice. The instructor side of the site contains editable PowerPoint slides, other solutions, and a test bank.
Reviews / Votes
This book gives students the practical knowledge and foundation of regression analysis. It is refreshing that the book includes twochapters the extend past linear regression to other types of analysis. -- Margaret Ralston
More details
Language
English
Place of publication
Thousand Oaks
United States
Target group
College/higher education
Dimensions
Height: 254 mm
Width: 178 mm
Weight
497 gr
ISBN-13
978-1-5443-3970-2 (9781544339702)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Author
University of Wisconsin-Milwaukee, USA
University of Wisconsin, Milwaukee, USA
Content
Chapter 1 Introduction
Chapter 2 Fundamentals of Multiple Regression
Chapter 3 Categorical Independent Variables in Multiple Regression: Dummy Variables
Chapter 4 Multiple Regression with Interaction
Chapter 5 Logged Variables in Multiple Regression
Chapter 6 Nonlinear Relationships in Multiple Regression
Chapter 7 Categorical Dependent Variables: Logistic Regression
Chapter 8 Count Dependent Variables: Poisson Regression
Chapter 9 A Brief Tour of Some Related Methods
Chapter 2 Fundamentals of Multiple Regression
Chapter 3 Categorical Independent Variables in Multiple Regression: Dummy Variables
Chapter 4 Multiple Regression with Interaction
Chapter 5 Logged Variables in Multiple Regression
Chapter 6 Nonlinear Relationships in Multiple Regression
Chapter 7 Categorical Dependent Variables: Logistic Regression
Chapter 8 Count Dependent Variables: Poisson Regression
Chapter 9 A Brief Tour of Some Related Methods