An Easy Guide to Research Design and SPSS® 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®, 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.
Table of Content
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
About the author
Dennis M. Goff received his Ph D in Experimental Psychology from Virginia Tech in 1985. He has been teaching and conducting research at Randolph College (formerly Randolph-Macon Woman’s College) since 1986. He specializes in teaching and learning in statistics and developmental psychology with a burgeoning interest in evolutionary psychology. In the past 27 years, he has mentored hundreds of senior psychology majors as they completed their independently designed research projects. In recent years, all of those seniors have presented their work at regional conferences, and a few have earned recognition for best undergraduate research projects. He is a Fellow of the Association for Psychological Science. He has been recognized at Randolph by being named a Charles A. Dana Professor of Psychology and given the Gillie A. Larew Award for Teaching Excellence and the Katherine Graves Davidson Award for Excellence in Promoting the College.
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