Design and Analysis in Educational Research Using jamovi

Kamden K. Strunk is an Associate Professor of Educational Research at Auburn University, where he primarily teaches quantitative methods. His research focuses on intersections of racial, sexual, and gender identities, especially in higher education. He is also a faculty affiliate of the Critical Studies Working Group at Auburn University.Mwarumba Mwavita is an Associate Professor of Research, Evaluation, Measurement, and Statistics at Oklahoma State University where he teaches quantitative methods. He is also the founding Director of Center for Educational Research and Evaluation (CERE) at Oklahoma State University.

"This text seems to capture the elements often found in multiple, separate sources (e.g., epistemology, research design, analysis, use of statistical software, and considerations for social justice/equity) and combines them in one text. This is so helpful, useful, and needed!" -- Sara R. Gordon, Ph.D., Associate Professor, Center for Leadership and Learning, Arkansas Tech University, USA"Strunk and Mwavita introduce fundamental elements of the research process and illustrate statistical analyses in the context of research design. Strunk and Mwavita provide illustrative examples that are realistic and accessible to those seeking a strong foundation in good research practices." -- Forrest C. Lane, Ph.D., Associate Professor and Chair, Department of Educational Leadership, Sam Houston State University, USA"Strunk and Mwavita provide a sound introductory text that is easily accessible to readers learning applied analysis for the first time." -- James Schreiber, Ph.D., Professor, School of Nursing, Duquesne University, USA

• PART 1. BASIC ISSUES 1. Basic Issues in Quantitative Educational Research 2. Sampling & Basic Issues in Research Design 3. Basic Educational Statistics; PART 2. NULL HYPOTHESIS SIGNIFICANCE TESTING 4. Introducing the Null-Hypothesis Significance Test 5. Comparing a Single Sample to the Population using the one-sample z-test and one-sample t-test; PART 3. BETWEEN-SUBJECTS DESIGNS 6. Comparing Two Samples Means: The Independent Samples t-test 7. Independent Samples t-test Case Studies 8. Comparing More Than Two Means Using the One-Way ANOVA 9. One-way ANOVA Case Studies 10. Comparing Means Across Two Independent Variables: The Factorial ANOVA 11. Factorial ANOVA Case Studies; PART 4. WITHIN-SUBJECTS DESIGNS 12. Comparing Two Within-Subjects Scores using the Paired Samples t-test 13. Paired Samples t-test Case Studies 14. Comparing More than Two Points from Within the Same Sample: The Within-Subjects ANOVA 15. Within-Subjects ANOVA Case Studies 16. Mixed Between- and Within-Subjects Designs using the Mixed ANOVA 17. Mixed ANOVA Case Studies; PART 5. CONSIDERING EQUITY IN QUANTITATIVE RESEARCH 18. Quantitative Methods for Social Justice and Equity