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An EasyGuide to Research Design and SPSS (R) is an essential resource for students to successfully navigate and complete research projects. Using a clear, concise, and conversational writing style, authors Beth M. Schwartz, Janie H. Wilson, and Dennis M. Goff cover all of the most basic and common designs and analyses that students need to know for appropriately testing a hypothesis. The handbook includes step-by-step instructions accompanied by ample screenshots for working with data in SPSS (R), along with guidance on interpreting outputs and formatting results in APA style. The Second Edition features a streamlined organization, updated references, and new content on factorial designs, effect size, and G*Power.

An EasyGuide to Research Design & SPSS

Preface

About the Authors

SECTION I. OVERVIEW OF BASIC DESIGN DECISIONS

1. The Marriage of Stats and Methods: 'til Death Do They Part

We Want to Help

Basic Steps of Research

Summary

2. Nominal, Ordinal, Interval, or Ratio: Why Your Type of Data Really Does Matter

Nominal Data

Ordinal Data

Interval Data

Ratio Data

Summary

3. Designing Your Hypothesis: To KISS (Keep It Simple, Student) or to Complicate Matters

How Many Variables Should I Include?

How Many Participants Should I Include?

How Many Independent Variables Should I Include?

Including More Than One Independent Variable

Choosing the Number of Levels of Each Variable

Choosing Your Dependent Variables

Avoiding the Unmeasurable Dependent Variables

How Many Dependent Variables to Include

Summary

SECTION II. YOUR BASIC SPSS TOOLBOX

4. Why SPSS and Not Other Software, Your Calculator, Fingers, or Toes

5. Handling Your Data in SPSS: Columns, and Labels, and Values . . . Oh My!

The Structure of SPSS

When to Create Your Data File: Yes, Even Before Data Collection

Setting Up Your Data File

Importing Data

Naming and Labeling Your Variables

How to Keep Track and Remember the Details of Your Data File

Creating New Variables in Your Data File: Transformations

Calculating a Total or Mean Score

Recording Variables

Conducting Analyses With Only Part of Your Collected Data: Split File and Select Cases

Summary

6. Descriptive Statistics: Tell Me About It

Describing Nominal Data

Describing Ordinal Data

Describing Interval or Ratio Data

Describing Data With Two Samples

Summary

SECTION III. DESIGNS, STATISTICS, INTERPRETATION, AND WRITE-UP IN APA STYLE

7. Between-Groups Designs: Celebrate Your Independence!

One IV, Two Levels

Between Groups With Two Levels of an IV

Independent-Samples t-Test With a Quasi-IV

Between Groups With More Than Two Levels of an IV

Between Groups With More Than One IV

Summary

8. Repeated-Measures Designs: Everybody Plays!

One Independent Variable With Two Levels

Expanding the Number of Levels for Your Independent Variable

Adding Another Factor: Within-Subjects Factorial Designs

Summary

9. Advanced Research Designs: Complicating Matters

Mixed Designs: One Between Variable and One Repeated-Measures Variable

A Multivariate Design: Measuring It All Including More Than One Dependent Variable in Your Design

ANCOVA

Summary

10. Correlational Analysis: How Do I Know If That Relationship Is Real?

Correlational Analysis: Two Variables

Prediction With Two Variables: Simple Linear Regression

Prediction With Several Variables: Multiple Linear Regression

Summary

11. Chi Square: Staying on the Same Frequency

What Do You Expect?

One-Way Chi Square With More Than Two Levels

Two-Way Chi Square

Summary

12. How Many Participants Do You Need? More Power to You!

Finding Power in SPSS's General Linear Model

Using G*Power to Find Power

Planning Sample Sizes for Your Future Research

Summary

SECTION IV. A SUMMARY

13. Mapping Your Decisions: You Can Get There From Here

Making Basic Decisions About Your Design

Data With Distinct Groups

Interval or Ratio Data With Many Levels

Summary

14. APA Results Sections

t-Test for Independent Samples (True IV)

t-Test for Independent Samples (Pseudo-IV)

One-Way ANOVA for Independent Groups (True IV)

t-Test for Correlated Samples

One-Way ANOVA for Correlated Groups (Repeated Measures)

Factorial ANOVA for Correlated Groups (Repeated Measures)

Factorial ANOVA for Mixed Groups

Factorial ANOVA for Independent Groups

Analysis of Covariance

Pearson's r Correlation

Pearson's r Correlation and Simple Regression

One-Way c2

Two-Way c2

15. Frequently Asked Questions: Did I Do That?

Questions About Research Design

Questions About Analyzing Your Data

Questions About Interpreting Your Data and Presenting Your Results

Summary

Glossary

Index

References