Design and Analysis in Educational Research

<p>NEW: updated eResources, 'Case Studies for Teaching on Race, Racism and Black Lives Matter.' Please see Support Material tab to download the new resources.</p><p>This book presents an integrated approach to learning about research design alongside statistical analysis concepts. Strunk and Mwavita maintain a focus on applied educational research throughout the text, with practical tips and advice on how to do high-quality quantitative research.</p><p>Design and Analysis in Educational Research 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 <i>z</i> and <i>t</i>), and ANOVA designs, including more advanced designs like the factorial ANOVA and mixed ANOVA, 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. An online eResource is also available with data sets.</p><p>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. </p> <p>FRONTMATTER:</p><ol> <p> </p> <li>Acknowledgements</li> </ol><p>BASIC ISSUES</p><ol> <p> </p> <li>Basic Issues in Quantitative Educational Research</li> <p> </p> <li>Sampling & Basic Issues in Research Design</li> <p> </p> <li>Basic Educational Statistics</li> <p>NULL HYPOTHESIS SIGNIFICANCE TESTING</p> <p> </p> <li>Introducing the Null-Hypothesis Significance Test</li> <p> </p> <li>Comparing a Single Sample to the Population using the one-sample <i>z</i>-test and one-sample <i>t</i>-test</li> <p>BETWEEN-SUBJECTS DESIGNS</p> <p> </p> <li>Comparing two samples means: The independent samples <i>t</i>-test</li> <p> </p> <li>Independent samples <i>t</i>-test Case studies</li> <p> </p> <li>Comparing more than two means: The one-way ANOVA</li> <p> </p> <li>One-way ANOVA Case Studies</li> <p> </p> <li>Comparing means across two independent variables: The factorial ANOVA</li> <p> </p> <li>Factorial ANOVA Case Studies</li> <p>WITHIN-SUBJECTS DESIGNS</p> <p> </p> <li>Comparing two points from the same sample (within-subjects comparison) using the paired samples <i>t</i>-test</li> <p> </p> <li>Paired samples <i>t</i>-test Case studies</li> <p> </p> <li>Comparing more than two points from within the same sample: The within-subjects ANOVA</li> <p> </p> <li>Within-subjects ANOVA case studies</li> <p> </p> <li>Mixed between- and within-subjects designs using the mixed ANOVA</li> <p> </p> <li>Mixed ANOVA Case Studies</li> <p>CONSIDERING EQUITY IN QUANTITATIVE RESEARCH</p> <p> </p> <li>Quantitative Methods for Social Justice and Equity: Theoretical and practical considerations</li> <p>APPENDICES</p> <ol> <p> </p> <li>A1 -<i> z</i> Table</li> <p> </p> <li>A2 -<i> t</i> Table</li> <p> </p> <li>A3 -<i> F</i> Table</li> <p> </p> <li>A4 -<i> HSD</i> Table</li> <p> </p> <li>B1 – Statistical Notation and Formulas</li> <p> </p> <li>References</li> </ol> </ol>