Design and Analysis in Quantitative Educational Research (2^nd Ed.) Univariate Designs in SPSS

Design and Analysis in Quantitative Educational Research: Univariate Designs in SPSS presents an integrated approach to learning about research design alongside statistical analysis concepts. The authors maintain a focus on applied educational research throughout the text, with practical tips and advice on how to do high-quality quantitative research.

This book teaches research design (including epistemology, research ethics, forming research questions, quantitative design, sampling methodologies, and design assumptions) and introductory statistical concepts (including descriptive statistics, probability theory, sampling distributions), basic statistical tests (like z and t), ANOVA designs, including more advanced designs like the factorial ANOVA and mixed ANOVA, simple linear regression, and multiple regression using SPSS for analysis. Designed specifically for an introductory graduate course in research design and statistical analysis, the book takes students through principles by presenting case studies, describing the research design principles at play in each study, and then asking students to walk through the process of analyzing data that reproduce the published results. The new edition has been updated to include the latest contemporary research developments, coverage of IBM SPSS Statistics version 29, and also features new case studies, many focused on race and racism as well as other equity and justice work, and additional content on covariance and correlation. An online eResource is also available with data sets.

This textbook is tailor-made for first-level doctoral courses in research design and analysis, and will also be of interest to graduate students in education and educational research.

Educational Research Basics 1. Basic Issues in Quantitative Educational Research 2. Equity and Justice in Quantitative Educational Research 3. Sampling & Basic Issues in Research Design 4. Basics in Educational Statistics; Null Hypothesis Significance Testing 5. Introducing the Null-Hypothesis Significance Test 6. Comparing a Single Sample to the Population Using the One-sample z-test and One-sample t-test; Between-Subjects Designs 7. Comparing Two Samples Using the Independent Samples t-test 8. Independent Samples t-test Case Studies 9. Comparing more than two means using the one-way ANOVA 10. One-way ANOVA Case Studies 11. Comparing Means Across Two Independent Variables Using the Factorial ANOVA 12. Factorial ANOVA Case Studies; Within-Subjects Designs 13. Comparing Two Points From the Same Sample (Within-subjects Comparison) Using the Paired Samples t-test 14. Paired Samples t-test Case studies 15. Comparing More Than Two Points from Within the Same Sample Using The Within-Subjects ANOVA 16. Within-subjects ANOVA Case Studies 17. Mixed Between- and within-subjects Designs Using the Mixed ANOVA 18. Mixed ANOVA Case Studies; Regression Designs 19. Correlation and Simple Linear Regression 20. Multiple Regression Analysis 21. Multiple Regression Analysis Case Studies

Kamden K. Strunk is a faculty in the School of Education at Virginia Commonwealth University focused on research methodologies. His research focuses on critical quantitative methodologies, queer and trans studies in education, and equity and justice in education.

Mwarumba Mwavita is faculty in the College of Education and Human Sciences at Oklahoma State University focused on quantitative methodologies. He is also the Founding Director of the Center for Educational Research and Evaluation (CERE) at Oklahoma State University.