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Practical Statistics
A Quick and Easy Guide to IBM® SPSS® Statistics, STATA, and Other Statistical Software
- David Kremelberg - DK Statistical Consulting Inc., University of Connecticut, Storrs, USA
September 2013 | 528 pages | SAGE Publications, Inc
Making statistics—and statistical software—accessible and rewarding
This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS.
This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.
This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS.
This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.
About the Authors
Preface
Acknowledgments
Introduction
Chapter 1: An Introduction to Statistics & Quantitative Methods
Chapter 2: An Introduction to IBM® SPSS® Statistics and Stata
Chapter 3: Descriptive Statistics
Chapter 4: Pearson's r, Chi-square, t-Test, and ANOVA
Chapter 5: Linear Regression
Chapter 6: Logistic, Ordered, Multinomial, Negative Binomial, and Poisson Regression
Chapter 7: Factor Analysis
Chapter 8: Time-Series Analysis
Chapter 9: Hierarchical Linear Modeling
Chapter 10: Structural Equation Modeling
Appendix A: Selecting the Appropriate Test
Appendix B: Tables of Significance
Appendix C: Additional Statistical Tests and Equations
Glossary
Index
The book is an excellent source for my Management doctoral students working on applied research involving regression. I partcilarly liked the exposition of difficult concepts using to the point phrases followed by easy to comprehend mathematical notaion and/or formulae. Excellent reference textbook!
School Of Management, Walden University
April 23, 2010
