Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results

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Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results

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內容描述

Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles.wwwStatsInResearch.com, is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors.Advanced Statistics in Research does not show how to perform statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more.Advanced Statistics in Research assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples.Need help writing up your results? Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more).Advanced Statistics in Research is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.

作者介紹

Author. Larry Hatcher Ph.D. is author or co-author of five textbooks that show how to perform statistical analyses using the SAS and JMP applications. These include A Step-by-Step Approach to Using SAS for Univariate & Multivariate Statistics (co-authored with Norm O'Rourke and Edward Stepanski) and the widely-cited A Step-By-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling. Larry earned his doctorate in industrial and organizational psychology from Bowling Green State University in 1983. He won the Cecil M. Freeburne Award for Excellence in Teaching at Bowling Green State University in 1981, was named the Outstanding Junior Professor at Winthrop University in 1987, and won the Best Paper Prize for an article published in the Journal of Organizational Behavior (co-authored by Tim Ross) in 1991. He is currently Professor of Psychology at Saginaw Valley State University where he teaches courses on elementary and advanced statistics.