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.
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.
Readers say about Hatcher''s books:
is worth the time spending on
Best statistics book I''ve ever had
the author explains difficult stats concepts very well and in an easy-to-understand way
Very useful, readable book
Explains concepts in a conventional (as opposed to theoretical way)
wonderful explanations in basic English
The Easiest Guide to the Nastiest Statistics
Advanced Statistics in Research is the easy-to-understand introduction to the scariest statistical procedures: multiple regression, discriminant analysis, logistic regression, MANOVA, ANOVA, ANCOVA, factor analysis, path analysis, structural equation modeling, meta-analysis, and more. It does not show how to
perform statistical analyses--
it shows how to read and understand the results from these analyses as they are typically reported in published research articles.
* Little or no background is required--introductory chapters review the basics of
research design and elementary statistics.
* Complex matrix-algebra formulas are avoided--all procedures, results, and
statistical symbols are explained in simple, nontechnical terms.
* Concepts are illustrated with engaging, easy-to-understand examples.
Traditional practices and best practices.
Advanced Statistics in Research illustrates the popular practices that researchers have traditionally followed when writing up their results for manuscripts and presentations. It also illustrates the newer conventions that are currently recommended by the
Publication Manual of the American Psychological Association, the APA''s
on Statistical Inference, and similar authoritative sources.
Statistical significance, confidence intervals, and effect size. Readers will learn how to correctly interpret and report significance tests, confidence intervals, effect size, and replication statistics such as
Meta-analysis. A comprehensive but user-friendly chapter on meta-analysis finally makes this ultra-important topic accessible to readers at all levels.
Writing the Results section. Students and researchers will see many examples of text, tables, and figures prepared according to the
Publication Manual of the American Psychological Association. An
Appendix reviews the basics of APA format for the
Results section of journal articles. Sample write-ups range from the basic (e.g., means and standard deviations) to advanced and multivariate statistics (e.g., factor analysis and structural equation modeling).
Figures in APA format. Readers will see many APA-style examples of charts and graphs for the
Results section: histograms, bar charts with error bars, box-and-whisker charts, scatterplots, funnel plots, path diagrams, and more.
Free exercises and more at companion web site. Students and instructors will find free PDF downloads of chapter exercises, PowerPoint® slides, and other supplementary materials at
StatsInResearch.com. A free 600-item test bank is available to instructors
Audience. Appropriate as a textbook in upper-level undergraduate courses, as a textbook in graduate courses, or as a stand-alone reference for students and researchers in the social and behavioral sciences, health, education, and business.
Larry Hatcher, Ph.D. is Professor of Psychology at Saginaw Valley State University in Saginaw, Michigan. He is author or co-author of six textbooks on statistics and data analysis, including A Step-by-Step Approach to Using SAS® for Univariate & Multivariate Statistics and the widely-cited A Step-by-Step Approach to Using the SAS® System for Factor Analysis and Structural Equation Modeling.