# Using SPSS for Windows and Macintosh : Analyzing and Understanding Data

**by**Green, Samuel B.; Salkind, Neil J.

### 9780205020409

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It gives assumptions for each type of statistical function, as well as step-by-step instructions, examples, and APA style reporting of results.

## Summary

**For courses in Introductory Statistics and Research Methods courses using SPSS.**

**Using SPSS** guides students through the most basic of SPSS techniques using step-by-step descriptions, presents statistical techniques and instruction on how to conduct statistical analyses, and explains in detail how to avoid all the obstacles common in the study of statistics.

The development of easy-to-use statistical software like SPSS has changed the way statistics is being taught and learned. Students can make transformations of variables, create graphs of distributions of variables, and select among statistical analyses all at the click of a button. However, even with these advancements, students sometimes still find statistics to be an arduous task.

They continue to be faced with many potential obstacles and they might feel overwhelmed and stressed rather than challenged and excited about the potential for mastering these important skills. **Samuel Green** and **Neil Salkind** have written a text to specifically address these issues.

## Author Biography

Neil J. Salkind is a professor emeritus of educational psychology at the University of Kansas where he taught for 35 years. He received his degree from the University of Maryland's Institute for Child Study and has published numerous journal articles and books, among them being *Using SPSS* with Sam Green (Prentice Hall), *Exploring Research* (Prentice Hall) and *Statistics for People Who (Think They) Hate Statistics* (Sage). He is active in the Society for Research in Child Development where he edited the journal *Child Development Abstracts & Bibliography*, and the American Psychological Association. He lives in Lawrence, KS.

## Table of Contents

Preface

**Part I ** **Introducing SPSS **

**Unit 1 Getting Started with SPSS **

Lesson 1 Starting SPSS

Lesson 2 The SPSS Main Menus and Toolbar

Lesson 3 Using SPSS Help

Lesson 4 A Brief SPSS Tour

**Unit 2 Creating and Working with Data Files **

Lesson 5 Defining Variables

Lesson 6 Entering and Editing Data

Lesson 7 Inserting and Deleting Cases and Variables

Lesson 8 Selecting, Copying, Cutting, and Pasting Data

Lesson 9 Printing and Exiting an SPSS Data File

Lesson 10 Exporting and Importing SPSS Data

Lesson 11 Validating SPSS Data

**Unit 3 Working with Data **

Lesson 12 Finding Values, Variables, and Cases

Lesson 13 Recoding Data and Computing Values

Lesson 14 Sorting, Transposing, and Ranking Data

Lesson 15 Splitting and Merging Files

**Unit 4A Working with SPSS Charts and Output for Windows **

Lesson 16A Creating an SPSS Chart

Lesson 17A Enhancing SPSS Charts

Lesson 18A Using the Viewer and Pivot Tables

**Unit 4B Working with SPSS Charts and Output for Macintosh **

Lesson 16B Creating an SPSS Chart

Lesson 17B Enhancing SPSS Charts

Lesson 18B Using the Viewer and Pivot Tables

**Part II Working with SPSS Procedures **

**Unit 5 Creating Variables and Computing Descriptive Statistics **

Lesson 19 Creating Variables

Lesson 20 Univariate Descriptive Statistics for Qualitative Variables

Lesson 21 Univariate Descriptive Statistics for Quantitative Variables

**Unit 6 t Test Procedures **

Lesson 22 One-Sample t Test

Lesson 23 Paired-Samples t Test

Lesson 24 Independent-Samples t Test

**Unit 7 Univariate and Multivariate**

Analysis-of-Variance Techniques

Lesson 25 One-Way Analysis of Variance

Lesson 26 Two-Way Analysis of Variance

Lesson 27 One-Way Analysis of Covariance

Lesson 28 One-Way Multivariate Analysis of Variance

Lesson 29 One-Way Repeated-Measures Analysis of Variance

Lesson 30 Two-Way Repeated-Measures Analysis of Variance

**Unit 8 Correlation, Regression, and Discriminant Analysis Procedures **

Lesson 31 Pearson Product-Moment Correlation Coefficient

Lesson 32 Partial Correlations

Lesson 33 Bivariate Linear Regression

Lesson 34 Multiple Linear Regression

Lesson 35 Discriminant Analysis

**Unit 9 Scaling Procedures **

Lesson 36 Factor Analysis

Lesson 37 Internal Consistency Estimates of Reliability

Lesson 38 Item Analysis Using the Reliability Procedure

**Unit 10 Nonparametric Procedures **

Lesson 39 Binomial Test

Lesson 40 One-Sample Chi-Square Test

Lesson 41 Two-Way Contingency Table Analysis Using Crosstabs

Lesson 42 Two Independent-Samples Test: The Mann-Whitney U Test

Lesson 43 K Independent-Samples Tests: The Kruskal-Wallis and the Median Tests

Lesson 44 Two Related-Samples Tests: The McNemar, the Sign, and the Wilcoxon Tests

Lesson 45 K Related-Samples Tests: The Friedman and the Cochran Tests

Appendix A Data for Crab Scale and Teacher Scale

Appendix B Methods for Controlling Type I Error across Multiple Hypothesis Tests

Appendix C Selected Answers to Lesson Exercises

References

Index