An edition of Linear Regression Analysis (2015)

Linear Regression Analysis

Assumptions and Applications

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Last edited by MARC Bot
November 13, 2020 | History
An edition of Linear Regression Analysis (2015)

Linear Regression Analysis

Assumptions and Applications

  • 0 Ratings
  • 2 Want to read
  • 0 Currently reading
  • 0 Have read

Social work and other social and behavioral science students and researchers need to have a suite of research tools to conduct studies. Regression analysis is a popular tool that is used in numerous studies to examine statistical relationships among variables. Yet there are few books that offer straightforward and easy-to-follow instruction regarding this type of analysis. Most books rely too much on mathematical and symbolic representations of regression analysis, even though many students do not have a sufficient background in mathematics and are often put off by the high level of sophistication required to master these techniques. This book offers a conceptual and software-driven approach to understanding linear regression analysis, with only a slight familiarity with algebra required even for self-study. Students and researchers will find this to be an accessible, yet thorough, introduction to the linear regression model.

Publish Date
Language
English
Pages
240

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Edition Availability
Cover of: Linear Regression Analysis
Linear Regression Analysis: Assumptions and Applications
May 5, 2015, NASW Press, National Association of Social Workers
Paperback in English

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Book Details


Table of Contents

-A review of some elementary statistical concepts --
-Simple linear regression --
-Multiple linear regression analysis --
-The ANOVA table and goodness-of-fit --
-Comparing linear regression models --
-Dummy variables in linear regression models --
-Specification errors in linear regression models --
-Measurement errors in linear regression models --
-Collinearity and multicollinearity --
-Nonlinear associations and interaction terms --
-Heteroscedasticity and autocorrelation --
-Influential observations : leverage points and outliers --
-A brief introduction to logistic regression --
-An introduction to multilevel models --
-Conclusion.

Edition Notes

A student who is learning regression for the first time will find how impressing, clear and concise this book is. It goes through stata and spss processes in setting up and interpreting regression data. This book is highly recommended to both students and professors.

Includes bibliographical references and index.

Published in
Washington, USA

Classifications

Dewey Decimal Class
519.5/36
Library of Congress
HV29 .H64 2015

Contributors

Author
John P. Hoffmann
Co-Author
Kevin Shafer

The Physical Object

Format
Paperback
Pagination
xiv, 226 pages : illustration ; 23 cm
Number of pages
240
Dimensions
10 x 7 x 1 inches
Weight
15 ounces

ID Numbers

Open Library
OL26857088M
ISBN 10
0871014572
ISBN 13
9780871014573
LCCN
2014041003
OCLC/WorldCat
899949368
Goodreads
28653993

Work Description

Linear Regression Analysis: Assumptions and Applications is designed to provide students with a straightforward introduction to a commonly used statistical model that is appropriate for making sense of data with multiple continuous dependent variables. Using a relatively simple approach that has been proven through several years of classroom use, this text will allow students with little mathematical background to understand and apply the most commonly used quantitative regression model in a wide variety of research settings. Instructors will find that its well-written and engaging style, numerous examples, and chapter exercises will provide essential material that will complement classroom work. Linear Regression Analysis may also be used as a self-teaching guide by researchers who require general guidance or specific advice regarding regression models, by policymakers who are tasked with interpreting and applying research findings that are derived from regression models, and by those who need a quick reference or a handy guide to linear regression analysis.

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History

Download catalog record: RDF / JSON
November 13, 2020 Edited by MARC Bot import existing book
April 21, 2019 Edited by Kaustubh Chakraborty Added new cover
April 21, 2019 Edited by Kaustubh Chakraborty Added new book
April 21, 2019 Created by Kaustubh Chakraborty Added new book.