# Using SPSS to Solve Statistical Problems: A Self-Instruction Guide

## David M. Shannon; Mark A. Davenport

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This book helps users learn to use a variety of SPSS procedures to solve statistical problems and analyze the output. Its step-by-step, screen-by-screen approach explores every SPSS dialog box and window that SPSS users will encounter as they solve statistical problems. It is designed as a self-instructional guide so users can easily follow and learn SPSS while actually using the program. The author(s) provide a brief rationale and real-life examples for each statistical procedure addressed in the book. Presents an illustration of each procedure— followed with a thorough discussion and interpretation of the output generated using SPSS. Topics covered include: Retrieving and Saving SPSS Files; Data Entry and Definition; Importing and Merging Data Files; Frequency Analysis; Measures of Central Tendency and Variability; Selecting and Describing Subgroups; Recoding Variables; Computing New Variables; Reliability Analysis; Introduction to Hypothesis Testing; Crosstabulation of Variables; Displaying & Describing Relationships; T-Tests; One-Way and Factorial ANOVA; Paired-Samples T-Test; Within-Subjects and Mixed -Model ANOVA; and Bivariate and Multiple Regression. Intended as a supplemental self-instructional guide for those learning SPSS to solve statistical problems.

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From the Inside Flap:

Preface

The motivation for writing this text comes from ten years of experience with students enrolled in beginning statistics classes. Students in these classes have had to deal with the challenges of learning not only statistical concepts, but also how to use the computer software (SPSS) that will guide them through their statistical analyses. Whether you are a student learning about statistics for the first time or an experienced researcher who has used statistics throughout your career, you are likely to have many encounters with software such as SPSS® for Windows.

Such programs have become more "user friendly" over the years with the introduction of graphical menus and windows. The modern graphical user interface is a far cry from the "old days" of writing code and punching cards. Nevertheless, learning to use a new software program is still difficult, especially when you don't use the program on a regular basis. Learning to use the software package, however, is just the first step. You also need to be able to make sense of the output generated by the software program so you can incorporate it accurately in your research reports. We have written this book to assist you with two tasks: 1) using SPSS to solve statistical problems and 2) making sense of the output.

We believe this book will serve as a valuable supplement in a beginning or intermediate statistics course. Becoming proficient with SPSS for Windows will make the process of statistical analysis less time consuming and painstaking, allowing you more time to think about research design and analysis, and strengthening the overall quality of your work. An overview of the text organization and key features follows. SPECIAL FEATURES AND TEXT ORGANIZATION

Step-by-Step Illustration of Statistical Procedures. For each statistical procedure addressed in this book, we provide a brief rationale for its use as well as a few examples. In most cases, these examples are drawn from real data gathered from graduate students enrolled in a beginning statistics course. Each statistical procedure is presented in a step-by-step manner using SPSS for Windows. Each menu and screen encountered in these steps has been captured and used to further illustrate the process. Following the illustration of each procedure, we thoroughly discuss and interpret the output generated by SPSS.

Data disk. A data disk is included with this text. It contains all the data files you will need to follow along with each chapter's illustrations. These files are carefully named to correspond with the chapters in which they are used. For example, the data used in Chapter 4 is identified as "chap 4 data." These data files have been created from a larger data set pertaining to graduate students enrolled in a beginning statistics course. To make things easier for you, we have included only the variables you will need for the chapter's illustrations.

Practice Exercises. Practice Exercises are included at the end of each chapter so you can apply and expand upon what you have learned. These exercises are brief and focus on the specific procedures illustrated in that chapter. The answers to these exercises are provided in Appendix D so you can check your work.

Organization of the text. This text is divided into seven sections. The first section (Chapters 1 through 4) provides an overview of SPSS, how to retrieve and save SPSS files, how to define variables and create a data set, and how to import and merge data files. In Section 2 (Chapters 5 through 7), we explore various data analysis procedures that are used to summarize and describe data. These procedures include frequency analysis and descriptive statistics. The third section includes three chapters (8 through 10), which illustrate how to transform variables, create new variables, and estimate the reliability of variables. The variables created in this section are used throughout the remainder of the text.

The fourth section consists of just one chapter that focuses on the process of hypothesis testing. This chapter serves as a transition into the statistical procedures used to address hypotheses and research questions in the remaining sections of the text.

Section 5 (Chapters 12 through 14) explores a few procedures used to measure relationships among variables. These correlational procedures, which include chi-square, Pearson, and Spearman correlation, are examined as they pertain to different types of variables. We also include a chapter on displaying relationships using scatterplots.

We begin making comparisons between groups in Section 6 (Chapters 15 through 17). Statistical procedures used to make these comparisons include t-tests, one-way ANOVA, and factorial ANOVA. Within-subjects designs are discussed in Section 7 (Chapters 18 through 20). These three chapters focus on paired t-tests, repeated-measures ANOVA, and mixed ANOVA designs. We conclude with Section 7 (Chapters 21 through 23), which provides an overview of regression analysis. These chapters illustrate bivariate and multiple regression analysis as well as the use of categorical predictors in regression.

Merrill has a statistics website that includes, among other things, web links to statistics tools and additional data sets. To link to this site, go to prenhall/shannon. ACKNOWLEDGMENTS

First of all, we would like to acknowledge the students from our statistics classes over the past ten years who have requested that such a book be written. We have observed these students struggle and succeed while learning statistics and SPSS. These students have been extremely helpful throughout the creation and development of this text. They have used drafts to guide their learning of SPSS and have provided very thoughtful feedback as to how these drafts could be improved.

We would also like to express our gratitude to the reviewers who have carefully and thoughtfully read several drafts and offered constructive feedback regarding our progress. Their expertise and experience in teaching statistics and using statistical software contributed greatly to the organization and content of this text. These reviewers are: Tom Coombs, Duke University; Joe Cornett, Texas Tech University; Beverly J. Dretzke, University of Wisconsin-Eau Claire; Jimmie C. Fortune, Virginia Tech; Thomas T Frantz, SUNY-Buffalo; Gretchen Guiton, University of Southern California; Wayne 1. Gordon, Western Illinois University; Robert Hale, Pennsylvania State University; Basil Hamilton, Texas Woman's University; and Bill Roweton, Chadron State College.

We further acknowledge Kevin Davis, Executive Editor from Prentice Hall, for working with us throughout this project. His critical analysis of our work and recommendations improved the content and organization of this book. In addition, we thank Holly Jennings for her assistance in the coordination of feedback and editorial assistance with the manuscript. Furthermore, we would like to thank Amy Gehl and the staff from Carlisle Communications for their careful editing throughout the production phase. They were instrumental in transforming the original manuscript pages into this book.

Finally, we thank you for using this book and hope it allows you to use SPSS for Windows more proficiently and make sense of all the output you generate. As you follow along with the illustrations in this book, we encourage you to jot down comments. Your feedback will help us to better understand how the next edition can be refined and improved. Please feel free to contact us at:

David M. Shannon
Auburn University email: shanndm@auburn

Mark A. Davenport
ACT, Inc. email: davenpor@act

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