The Chicago Guide to Writing about Multivariate Analysis

The Chicago Guide to Writing about Multivariate Analysis
Author :
Publisher : University of Chicago Press
Total Pages : 512
Release :
ISBN-10 : 9780226527840
ISBN-13 : 0226527840
Rating : 4/5 (840 Downloads)

Book Synopsis The Chicago Guide to Writing about Multivariate Analysis by : Jane E. Miller

Download or read book The Chicago Guide to Writing about Multivariate Analysis written by Jane E. Miller and published by University of Chicago Press. This book was released on 2008-04-15 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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