Book contents
- Research Methods and Applied Statistics
- Reviews
- Research Methods and Applied Statistics
- Copyright page
- Dedication
- Contents
- Guided Tour
- Preface
- Acknowledgments
- 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 and Required Libraries
- Further Reading
- Index
3 - Experimental vs. Correlational Studies, Measuring Constructs, and Internal Consistency Reliability
Published online by Cambridge University Press: 17 December 2025
Book contents
- Research Methods and Applied Statistics
- Reviews
- Research Methods and Applied Statistics
- Copyright page
- Dedication
- Contents
- Guided Tour
- Preface
- Acknowledgments
- 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 and Required Libraries
- Further Reading
- Index
Summary
Null hypothesis significance testing is reviewed along with how this method is used for testing hypotheses in research studies. Students are guided through the structures of experimental and correlational studies along with justifications for performing one method or the other. Factors involving choosing surveys, including considerations of reliability and validity, are discussed. Understanding what survey constructs (i.e., psychometric factors) are, how they are developed, and how they are scored are reviewed. Cronbach’s α and McDonald’s ω are reviewed as popular ways to measure the internal consistency reliability of subscales in a survey. Students are taught how to calculate these two statistics using SPSS and R.
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- Research Methods and Applied StatisticsA Practical Guide to Conducting Research, pp. 70 - 93Publisher: Cambridge University PressPrint publication year: 2025
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