This new text provides students with the background and the process of statistical analysis along with the nuts and bolts tools for applying specific statistical tools to data from research studies. McBride will help students to understand that statistics can be applied and used in day to day life, and she will make a direct connection between the process of research design and the tools employed in statistical analysis.
The text opens with introductory discussions of why psychologists conduct and analyze research before digging into the process of designing an experiment and performing statistical analyses.
This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance.
Packed with exercises, checklists, and how-to sections, the robust Lab Manual for Statistical Analysis by Dawn M. McBride and J. Cooper Cutting gives students hands-on guidance and practice for analyzing their own psychological research.
This practical, conceptual introduction to statistical analysis by award-winning teacher Andrew N. Christopher uses published research with inherently interesting social sciences content to help students make clear connections between ...
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This text takes a classic approach that emphasizes concepts and techniques for working out problems and intepreting results.
Along with significantly updated discussions of effect size and meta-analysis, this Eighth Edition continues to focus on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning ...
reading. Carroll, J.D., Green, P.E., & Chaturvedi, A. (1997). Mathematical tools for applied multivariate analysis: Revised edition. San Diego, CA: Academic Press. Fox, J. (2009). A mathematical primer for social statistics.
This lab manual serves as an additional resource for students and instructors in a research methods, statistics, or combined course where classroom and/or laboratory exercises are conducted.
Basic statistical concepts such as probability, estimation and inference, and their role in research design and analysis are presented in this volume.