IBM SPSS by Example 2/e

Alan Elliott is the Director of the Statistical Consulting Center at Southern Methodist University within the Department of Statistical Science. Previously he served as a statistical consultant in the Department of Clinical Science at the University of Texas Southwestern Medical Center at Dallas for 30 years. Elliott holds master's degrees in Business Administration (MBA) and Applied Statistics (MAS). He has authored or coauthored over 35 scientific articles and over a dozen books including the Directory of Microcomputer Statistical Software, Microcomputing with Applications, Using Norton Utilities, SAS Essentials, Applied Time Series Analysis, and Statistical Analysis Quick reference Guidebook with SPSS Examples. Elliott has taught university-level courses in statistics, statistical consulting, and statistical computing for over twenty-five years. Wayne A. Woodward, Ph.D., is a Professor of Statistics and chair of the Department of Statistical Science at Southern Methodist University. He is a fellow of the American Statistical Association and was the 2004 recipient of the Don Owen award for excellence in research, statistical consulting, and service to the statistical community. In 2007 he received the Outstanding Presentation Award given by the Section on Physical and Engineering Sciences at the 2007 Joint Statistical Meetings in Salt Lake City, Utah. In 2003 he was named a Southern Methodist University Distinguished Teaching Professor by the university's Center for Teaching Excellence, and he received the 2006-2007 Scholar/Teacher of the Year Award at SMU, an award given by the United Methodist Church. . Over the last 35 years he has served as statistical consultant to a wide variety of clients in the scientific community and has taught statistics courses ranging from introductory undergraduate statistics courses to graduate courses within the Ph.D. program in Statistics at Southern Methodist University. He has been funded on numerous research grants and contracts from government and industry to study such issues as global warming and nuclear monitoring. He has authored or coauthored over 70 scientific papers and four books.

Chapter 1: Introduction Getting the Most Out of IBM SPSS by Example A Brief Overview of the Statistical Process Understanding Hypothesis Testing, Power, and Sample Size Understanding the p-Value Planning a Successful Analysis Guidelines for Creating Data Sets Preparing Excel Data for Import Guidelines for Reporting Results Opening Data Files for Examples Chapter 2: Describing and Examining Data Example Data Files Describing Quantitative Data Describing Categorical Data Chapter 3: Creating and Using Graphs Introduction to SPSS Graphs Chart Builder Graphboard Template Chooser Legacy Plots Scatterplots Histograms Bar Charts Pie Charts Box Plots Chapter 4: Comparing One or Two Means Using the t-Test One-Sample t-Test Two-Sample t-Test Paired t-Test Chapter 5: Correlation and Regression Correlation Analysis Simple Linear Regression Multiple Linear Regression Chapter 6: Analysis of Categorical Data Contingency Table Analysis McNemar's Test Mantel-Haenszel Comparison Tests of Interrater Reliability Goodness-of-Fit Test Other Measures of Association for Categorical Data Chapter 7: Analysis of Variance and Covariance One-Way ANOVA Two-Way Analysis of Variance Repeated-Measures Analysis of Variance Analysis of Covariance Chapter 8: Non-parametric Analysis Procedures Spearman's Rho Mann-Whitney-Wilcoxon (Two Independent Groups Test) Kruskal-Wallis Test Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs Friedman's Test Chapter 9: Logistic Regression Simple Logistic Regression Multiple Logistic Regression Chapter 10: Factor Analysis Factor Analysis Examples

"This text not only helps the user to quickly navigate SPSS, but also provides critical aspects of each of the tests... I do not think that there is a better text for SPSS users who are looking for a quick introduction and succinct guidance." -- Philip J. Murphy, Monterey Institute of International Studies "All in all, [this text] will become an indispensable tool for anyone that seeks to use statistical procedures to analyze data and to report the same effectively." -- Tyrone Bynoe, University of the Cumberlands "[This text is] very readable and comprehensible for intermediate level students." -- Alan Davis, University of Colorado Denver