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Books > Reference & Interdisciplinary > Communication studies > Research methods
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What If There Were No Significance Tests? - Classic Edition (Hardcover, Classic Ed)
Loot Price: R5,514
Discovery Miles 55 140
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What If There Were No Significance Tests? - Classic Edition (Hardcover, Classic Ed)
Series: Multivariate Applications Series
Expected to ship within 10 - 15 working days
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The classic edition of What If There Were No Significance Tests?
highlights current statistical inference practices. Four areas are
featured as essential for making inferences: sound judgment,
meaningful research questions, relevant design, and assessing fit
in multiple ways. Other options (data visualization, replication or
meta-analysis), other features (mediation, moderation, multiple
levels or classes), and other approaches (Bayesian analysis,
simulation, data mining, qualitative inquiry) are also suggested.
The Classic Edition's new Introduction demonstrates the ongoing
relevance of the topic and the charge to move away from an
exclusive focus on NHST, along with new methods to help make
significance testing more accessible to a wider body of researchers
to improve our ability to make more accurate statistical
inferences. Part 1 presents an overview of significance testing
issues. The next part discusses the debate in which significance
testing should be rejected or retained. The third part outlines
various methods that may supplement significance testing
procedures. Part 4 discusses Bayesian approaches and methods and
the use of confidence intervals versus significance tests. The book
concludes with philosophy of science perspectives. Rather than
providing definitive prescriptions, the chapters are largely
suggestive of general issues, concerns, and application guidelines.
The editors allow readers to choose the best way to conduct
hypothesis testing in their respective fields. For anyone doing
research in the social sciences, this book is bound to become
"must" reading. Ideal for use as a supplement for graduate courses
in statistics or quantitative analysis taught in psychology,
education, business, nursing, medicine, and the social sciences,
the book also benefits independent researchers in the behavioral
and social sciences and those who teach statistics.
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