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

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The Storepaperoomates Retail Market » Catalog and Departments » Book » Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results
Product Description

Author: Hatcher Larry

Brand: Shadow Finch Media LLC

Edition: Illustrated

Format: Illustrated

Number Of Pages: 644

Details: Product Description

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.

Review

Readers say about Hatcher’s books:
wonderful discovery
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

From the Back Cover

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 Task Force 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 Prep.

Meta-analysis. A comprehensive but user-friendly chapter on meta-analysis finally makes this

Release Date: 07-01-2013

Package Dimensions: 37x254x1361

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