This psychology textbook teaches research methods and applied statistics in an accessible and conversational style so students can create and execute a well-informed, thorough research study using SPSS or R.
This psychology textbook teaches research methods and applied statistics in an accessible and conversational style so students can create and execute a well-informed, thorough research study using SPSS or R.
Anthony Girasoli is a lecturer in the Psychological Science department at Eastern Connecticut State University. His research is primarily rooted in cognitive psychology, where computer science meets theories and methods of psychology. Anthony is a member of the American Psychological Association and reviews articles for Computers & Education.
Inhaltsangabe
Preface Introduction 1. Developing a Research Study Proposal 2. Developing a Research Question and Hypotheses, Choosing Statistics, and Estimating the Sample Size 3. Experimental vs. Correlational Studies, Measuring Constructs, and Internal Consistency Reliability 4. Demographics, Creating Surveys, and Data Management 5. Qualitative and Mixed-Methods Approaches 6. Beginning Your Analysis: Descriptive Statistics and Correlations 7. Relationships Between Nominal Data: Chi-Square and McNemar's Tests 8. Comparing Means with Two Groups: The t and U Tests 9. Comparing Means with Multiple Groups: The Analysis of Variance (ANOVA) 10 Multiple Regression Analysis: Predicting a Continuous Variable 11. Binary Logistic Regression Analysis: Predicting a Dichotomous Variable 12. Data Visualization and Interpretation 13. Pulling it All Together: The Research Paper, the Research Poster, and Everything Appendix A: Installing R.
Preface Introduction 1. Developing a Research Study Proposal 2. Developing a Research Question and Hypotheses, Choosing Statistics, and Estimating the Sample Size 3. Experimental vs. Correlational Studies, Measuring Constructs, and Internal Consistency Reliability 4. Demographics, Creating Surveys, and Data Management 5. Qualitative and Mixed-Methods Approaches 6. Beginning Your Analysis: Descriptive Statistics and Correlations 7. Relationships Between Nominal Data: Chi-Square and McNemar's Tests 8. Comparing Means with Two Groups: The t and U Tests 9. Comparing Means with Multiple Groups: The Analysis of Variance (ANOVA) 10 Multiple Regression Analysis: Predicting a Continuous Variable 11. Binary Logistic Regression Analysis: Predicting a Dichotomous Variable 12. Data Visualization and Interpretation 13. Pulling it All Together: The Research Paper, the Research Poster, and Everything Appendix A: Installing R.
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