Research Methods and Statistics: An Integrated Approach by Janie H. Wilson and Shauna W. Joye offers a completely integrated approach to teaching research methods and statistics by presenting a research question accompanied by the appropriate methods and statistical procedures needed to address it. Research questions and designs become more complex as chapters progress, building on simpler questions to reinforce student learning. Using a conversational style and research examples from published works, this comprehensive book walks readers through the entire research process and includes ample pedagogical support for SPSS, Excel, and APA style.
Janie H. Wilson
I received my Ph.D. in Experimental Psychology from the University of South Carolina in 1994. Since that time, I have been teaching and conducting research at Georgia Southern University. In the classroom, I specialize in teaching and learning in statistics and research methods. Research interests include rapport in teaching based on empirical data on the first day of class, electronic communications, interactions with students in a traditional classroom, syllabus design, and the development and validation of the Professor-Student Rapport Scale. Publications include two recent texts with Sage: An EasyGuide to Research Presentations and I have had the pleasure to contribute numerous chapters to edited books and have co-edited several books related to teaching and learning. I publish extensively on the scholarship of teaching and learning and have offered over 60 conference presentations, including several invited keynote addresses. For 2016, I am honored to serve as the President of Division Two of APA. My primary initiative is sharing the science of psychology with students and the general community.
Section I: Foundations of Design and AnalysisChapter 1: The Scientific Method Empirical Data Step 1: Ask a Question Step 2: Read the Published Literature Step 3: Create a Method Step 4: Collect and Analyze Data Step 5: Answer the Research Question Step 6: Share Your Results Research in Psychology: APA StyleChapter 2: Ethical Research Ethical Treatment of Participants Assessing Risk to Participants Treating Participants Ethically Ethics After Testing Participants Who is Harmed by Unethical Behavior? Ethical Data-Collection MethodsChapter 3: Research Designs and Variables Correlational Design Experimental Design Random Assignment Extraneous Variables Internal Validity Levels of Measurement Summarizing Variables: Central Tendency Summarizing Variables: Variability SPSS: Summarizing VariablesChapter 4: Learning About a Population from a Sample Selecting a Sample Bias in a Sample Inferential Statistics Hypothesis Testing Significance p-values and Effect Size Power and Sample Size Degrees of FreedomSection II: Categorical Variables and Simple FrequencyChapter 5: One Variable With Frequency Data Research Design: Categorizing Participants SPSS: One-Way ?2 With Equal Expected Frequencies One-Way ?2 With Unequal Expected Frequencies SPSS: One-Way ?2 With Unequal ExpectationsChapter 6: Two Variables With Frequency Data Research Design: Two Categorical Variables Two-Way ?2: 2 X 3 Design Two-Way ?2: 2 X 2 DesignSection III: Research Without GroupingChapter 7: Examining Relationships Pearson's Correlation Coefficient (Pearson's r) Linear Relationships SPSS: Pearson's r (Nonsignificant Result) When Correlation Means Causation Scatterplot SPSS: Pearson's r (Significant Result) Inaccurate Pearson's r When Pearson's r Falsely Shows no Relationship When Pearson's r Falsely Shows a RelationshipChapter 8: Scale Development Pearson's r and Reliability of Measures Cronbach's Alpha and Reliability of Measures SPSS: Scoring and Interpreting Measures Reliability With Subjective Measures: Inter-Rater Reliability Pearson's r and ValidityChapter 9: Prediction Prediction and Correlation Prediction Using One Predictor SPSS: Linear Regression Multiple Linear Regression: Prediction With Two Predictors SPSS: Multiple Linear RegressionSection IV: Grouped Designs With Independent SamplesChapter 10: One Variable With Two Independent Groups Research Design: One IV With Two Levels SPSS: Independent-Samples t-test with an IV Outliers Using a Quasi-IV to Establish a Relationship SPSS: Independent-Samples t-test with a Quasi IVChapter 11: One Variable With More Than Two Independent Groups Design With More Than Two Groups SPSS: One-Way, Between-Groups ANOVA with an IV One-Way, Between-Groups ANOVA: Quasi-IV SPSS: One-Way, Between-Groups ANOVA With a Quasi-IVSection V: Grouped Designs with Related SamplesChapter 12: One Variable With Two Related Groups Testing the Same People Twice Problems with Testing the Same People Twice Solving Order Problems by Counterbalancing Avoid Confounds SPSS: Paired-Samples t-test (Experimental Design) SPSS: Paired-Samples t-Test (Correlational Design) Testing Different People (Matched Pairs) Matching Participants SPSS: Matched-Pairs t-TestChapter 13. One Variable with Repeated Measures: More than Two Groups One-Way, Repeated-Measures ANOVA (Experimental Design) Blind Scoring SPSS: One-Way, Repeated-Measures ANOVA One-Way, Repeated-Measures ANOVA (Correlational Design)Section VI: Advanced DesignChapter 14. Two Variables with Independent Samples Two-Way ANOVA with Nominal IVs SPSS: Two-Way, Between-Groups ANOVA (No Significant Interaction) Two-Way, Between-Groups ANOVA (Significant Interaction)AppendicesAppendix A. Power Analysis TableAppendix B. Graphing in Excel Scatterplots Bar Graphs Line Graphs Interaction GraphsAppendix C. APA-Style Manuscript Guidelines Key Elements in APA-Style Writing Common Mistakes and Tips for Writing Example Paper with Comments Example Paper without CommentsAppendix D. Selected Answers to Practice ItemsAppendix E. Glossary of TermsAppendix F. Index
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