"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.
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