Beth M. Schwartz, Janie H. Wilson, Dennis M. Goff

An EasyGuide to Research Design & SPSS

• Broschiertes Buch

Produktbeschreibung

Clear, concise and conversational, this second edition includes step-by-step instructions for working with data in SPSSÂ and covers the most common designs and analyses that students need to know to test a hypothesis and successfully complete their research project.

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Produktdetails

• EasyGuide Series
• Verlag: SAGE Publications Inc
• 2 Revised edition
• Seitenzahl: 312
• Erscheinungstermin: 15. Juni 2018
• Englisch
• Abmessung: 177mm x 236mm x 16mm
• Gewicht: 392g
• ISBN-13: 9781506385488
• ISBN-10: 1506385486
• Artikelnr.: 50009129

Autorenporträt

Beth M. Schwartz is the Provost and Professor of Psychology at Endicott College. Previously she served as Vice President for Academic Affairs and Provost and Professor of Psychology at Heidelberg University, in Tiffin, Ohio. Dr. Schwartz started her career on the faculty at Randolph College (founded as Randolph-Macon Woman¿s College) in Lynchburg, VA, where she served for 24 years. At Randolph she was the William E. and Catherine Ehrman Thoresen '23 Professor of Psychology and Assistant Dean of the College. She received a BA at Colby College (Maine) and a PhD in cognitive psychology at the State University of New York at Buffalo. Her scholarship focuses on the scholarship of teaching and learning/pedagogical research, in particular the issues surrounding academic integrity and honor systems. In addition to numerous professional presentations at conferences, she has published many book chapters and articles in a variety of scholarly journals, including the Journal of Higher Education, Ethics and Behavior,  Law and Human Behavior, and Applied Developmental Science. She has also edited and coauthored books, including Child Abuse: A Global View (Schwartz, McCauley, & Epstein, 2001), Optimizing Teaching and Learning  (Gurung & Schwartz, 2012), and Evidence-Based Teaching for Higher Education (Schwartz & Gurung, 2012). She is a member of the American Psychological Association (APA) and the American Psychological Society and is a Fellow of Division 2 of APA (Society for the Teaching of Psychology). She was an award-winning teacher at Randolph College, where she taught Introduction to Psychology, Research Methods, Cognitive Psychology, and the capstone course. She received the Award for Outstanding Teaching and Mentoring from the American Psych-Law Society, the Gillie A. Larew Award for Distinguished Teaching at Randolph College, the Katherine Graves Davidson Excellence in Scholarship Award from Randolph College, and the Distinguished Faculty Achievement Certificate from the State Council of Higher Education for Virginia.    

Inhaltsangabe

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