The Chicago Guide to Writing about Multivariate Analysis
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 Figures
List of Boxes
Preface
Acknowledgments
1. Introduction
Part I. Principles
2. Seven Basic Principles
3. Causality, Statistical Significance, and Substantive Significance
4. Five More Technical Principles
Part II. Tools
5. Creating Effective Tables
6. Creating Effective Charts
7. Choosing Effective Examples and Analogies
8. Basic Types of Quantitative Comparisons
9. Quantitative Comparisons for Multivariate Models
10. Choosing How to Present Statistical Test Results
Part III. Pulling It All Together
11. Writing Introductions, Conclusions, and Abstracts
12. Writing about Data and Methods
13. Writing about Distributions and Associations
14. Writing about Multivariate Models
15. Speaking about Multivariate Analyses
16. Writing for Applied Audiences
Appendix A. Implementing "Generalization, Example, Exceptions" (GEE)
Appendix B. Translating Statistical Output into Table and Text
Appendix C. Terminology for Ordinary Least Squares (OLS) and Logistic Models
Appendix D. Using a Spreadsheet for Calculations
Notes
Reference List
Index
Economics and Business: Business--Business Economics and Management Studies
Political Science: Political and Social Theory
Sociology: Methodology, Statistics, and Mathematical Sociology
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