Intermediate Statistics
A Modern Approach
Lawrence Erlbaum Associates Inc (Publisher)
Published on 1. February 1990
Book
Paperback/Softback
320 pages
978-0-8058-0492-8 (ISBN)
Article exhausted; check for reprint
Description
James Stevens' best-selling text, Intermediate Statistics, is written for those who use, rather than develop, statistical techniques. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving the results. SAS and SPSS are an integral part of each chapter. Definitional formulas are used on small data sets to provide conceptual insight into what is being measured.
The assumptions underlying each analysis are emphasized and the reader is shown how to test the critical assumptions using SPSS or SAS. Printouts with annotations from SAS or SPSS show how to process the data for each analysis. The annotations highlight what the numbers mean and how to interpret the results. Numerical, conceptual, and computer exercises enhance understanding. Answers are provided for half of the exercises.
The book offers comprehensive coverage of one-way, power, and factorial analysis of variance, repeated measures analysis, simple and multiple regression, analysis of covariance, and HLM. Power analysis is an integral part of the book. A computer example of real data integrates many of the concepts. Highlights of the Third Edition include:
A new chapter on hierarchical linear modeling using HLM6
A CD containing all of the book's data sets
New coverage of how to cross validate multiple regression results with SPSS and a new section on model selection (Chapter 6)
More exercises in each chapter.
Intended for intermediate statistics or statistics II courses taught in departments of psychology, education, business, and other social and behavioral sciences, a prerequisite of introductory statistics is required. An Instructor's Resource is available upon adoption. See www.researchmethodsarena.com .
The assumptions underlying each analysis are emphasized and the reader is shown how to test the critical assumptions using SPSS or SAS. Printouts with annotations from SAS or SPSS show how to process the data for each analysis. The annotations highlight what the numbers mean and how to interpret the results. Numerical, conceptual, and computer exercises enhance understanding. Answers are provided for half of the exercises.
The book offers comprehensive coverage of one-way, power, and factorial analysis of variance, repeated measures analysis, simple and multiple regression, analysis of covariance, and HLM. Power analysis is an integral part of the book. A computer example of real data integrates many of the concepts. Highlights of the Third Edition include:
A new chapter on hierarchical linear modeling using HLM6
A CD containing all of the book's data sets
New coverage of how to cross validate multiple regression results with SPSS and a new section on model selection (Chapter 6)
More exercises in each chapter.
Intended for intermediate statistics or statistics II courses taught in departments of psychology, education, business, and other social and behavioral sciences, a prerequisite of introductory statistics is required. An Instructor's Resource is available upon adoption. See www.researchmethodsarena.com .
More details
Language
English
Place of publication
Mahwah
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 229 mm
Width: 152 mm
ISBN-13
978-0-8058-0492-8 (9780805804928)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

James P. Stevens | Keenan A. Pituch | Tiffany A. Whittaker
Intermediate Statistics
A Modern Approach, Third Edition
Book
07/1999
2nd Edition
Lawrence Erlbaum Associates Inc
€46.00
Article exhausted; check for reprint
Persons
Author
The University of Texas at Austin, USA
The University of Texas at Austin
Emeritus, University of Cincinnati, USA
Content
Preface. 1. Introduction. 2. One Way Analysis of Variance. 3. Power Analysis. 4. Factorial Analysis of Variance. 5. Repeated Measures Analysis. 6. Simple and Mulitple Regression. 7. Analysis of Covariance. 8. Hierarchical Linear Modeling. Appendix A. Data Sets. Appendix B. Statistical Tables. Appendix C. Power Tables.