The Chicago guide to writing about multivariate analysis /

The Chicago guide to writing about multivariate analysis /

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Bibliographic Details
Author / Creator:	Miller, Jane E. (Jane Elizabeth), 1959-
Imprint:	Chicago : University of Chicago Press, 2005.
Description:	1 online resource (xv, 487 pages) : illustrations
Language:	English
Series:	Chicago guides to writing, editing, and publishing Chicago guides to writing, editing, and publishing.
Subject:	Technical writing. Multivariate analysis. Multivariate analysis. Technical writing.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11171304

Hidden Bibliographic Details
ISBN:	9780226527840 0226527840 9780226527826 0226527824 9780226527833 0226527832 0226527824 0226527832
Notes:	Includes bibliographical references (pages 445-455) and index. Print version record.
Summary:	Writing about multivariate analysis is a surprisingly common task. Researchers use these advanced statistical techniques to examine relationships among multiple variables, such as exercise, diet, and heart disease, or to forecast information such as future interest rates or unemployment. Many different people, from social scientists to government agencies to business professionals, depend on the results of multivariate models to inform their decisions. At the same time, many researchers have trouble communicating the purpose and findings of these models. Too often, explanations become bogged d.
Other form:	Print version: Miller, Jane E. (Jane Elizabeth), 1959- Chicago guide to writing about multivariate analysis. Chicago : University of Chicago Press, 2005 0226527824 9780226527826

Table of Contents:

Principles
Seven basic principles
Causality, statistical significance, and substantive significance
Five more technical principles
Tools
Creating effective tables
Creating effective charts
Choosing effective examples and analogies
Basic types of quantitative comparisons
Quantitative comparisons for multivariate models
Choosing how to present statistical test results
Pulling it all together
Writing introductions, conclusions, and abstracts
Writing about data and methods
Writing about distributions and associations
Writing about multivariate models
Speaking about multivariate analyses
Writing for applied audiences.