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
6 - Beginning Your Analysis: Descriptive Statistics and Correlations
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
From this point on in the textbook, the student researcher has finished collecting data for the study and is performing the data analysis. In this chapter, students learn how to clean and screen their data as well as checking the relationships between independent variables (IVs) and the dependent variable (DV). Basic statistical calculations (e.g., mean, standard deviation, normal distribution) are reviewed and applied. How to create survey factors (e.g., by calculating the total or mean of a subset of survey items) is reviewed. Instructions for calculating Pearson r among the hypotheses’ variables are provided along with reasoning (and warnings) for using correlations to investigate relationships among the data. Step-by-step instructions are provided for both SPSS and R.
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- Research Methods and Applied StatisticsA Practical Guide to Conducting Research, pp. 145 - 194Publisher: Cambridge University PressPrint publication year: 2025
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