Share
Presenting Statistical Results Effectively
September 2022 | 456 pages | SAGE Publications Ltd
Perfect for any statistics student or researcher, this book offers hands-on guidance on how to interpret and discuss your results in a way that not only gives them meaning, but also achieves maximum impact on your target audience. No matter what variables your data involves, it offers a roadmap for analysis and presentation that can be extended to other models and contexts.
Focused on best practices for building statistical models and effectively communicating their results, this book helps you:
- Find the right analytic and presentation techniques for your type of data
- Understand the cognitive processes involved in decoding information
- Assess distributions and relationships among variables
- Know when and how to choose tables or graphs
- Build, compare, and present results for linear and non-linear models
- Work with univariate, bivariate, and multivariate distributions
- Communicate the processes involved in and importance of your results.
Focused on best practices for building statistical models and effectively communicating their results, this book helps you:
- Find the right analytic and presentation techniques for your type of data
- Understand the cognitive processes involved in decoding information
- Assess distributions and relationships among variables
- Know when and how to choose tables or graphs
- Build, compare, and present results for linear and non-linear models
- Work with univariate, bivariate, and multivariate distributions
- Communicate the processes involved in and importance of your results.
Chapter 1: Some Foundation
Part A: General Principles of Effective Presentation
Chapter 2: Best Practices for Graphs and Tables
Chapter 3: Methods for Visualizing Distributions
Chapter 4: Exploring and Describing Relationships
Part B: The Linear Model
Chapter 5: The Linear Regression Model
Chapter 6: Assessing the Impact and Importance of Multi-category Explanatory Variables
Chapter 7: Identifying and Handling Problems in Linear Models
Chapter 8: Modelling and Presentation of Curvilinear Effects
Chapter 9: Interaction Effects in Linear Models
Part C: The Generalized Linear Model and Extensions
Chapter 10: Generalized Linear Models
Chapter 11: Categorical Dependent Variables
Chapter 12: Conclusions and Recommendations
Is your quantitative work so screamingly clear that your readers never misunderstand your figures, misread your tables, or get confused by your prose? If so, then don't waste your time with Andersen and Armstrong's thoughtful book about the effective presentation and interpretation of statistical results.
Albert J Weatherhead III University Professor and director of the Institute for Quantitative Social Science, Harvard University