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Chicago Guide to Writing about Multivariate Analysis

ISBN-10: 0226527832
ISBN-13: 9780226527833
Edition: 2005
Authors: Jane E. Miller
List price: $32.50
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Description: 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  More...

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Book details

List price: $32.50
Copyright year: 2005
Publisher: University of Chicago Press
Publication date: 8/1/2005
Binding: Paperback
Pages: 500
Size: 5.25" wide x 8.00" long x 0.75" tall
Weight: 1.782
Language: English

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 down in statistical jargon and technical details, and audiences are left struggling to make sense of both the numbers and their interpretation. Here, Jane Miller offers much-needed help to academic researchers as well as to analysts who write for general audiences." The Chicago Guide to Writing about Multivariate Analysis brings together advanced statistical methods with good expository writing. Starting with twelve core principles for writing about numbers, Miller goes on to discuss how to use tables, charts, examples, and analogies to write a clear, compelling argument using multivariate results as evidence. Writers will repeatedly look to this book for guidance on how to express their ideas in scientific papers, grant proposals, speeches, issue briefs, chartbooks, posters, and other documents. Communicating with multivariate models need never appear so complicated again.

List of Tables
List of Figures
List of Boxes
Preface
Acknowledgments
Introduction
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
Implementing "Generalization, Example, Exceptions" (GEE)
Translating Statistical Output into Table and Text
Terminology for Ordinary Least Squares (OLS) and Logistic Models
Using a Spreadsheet for Calculations
Notes
Reference List

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