Book contents
- Frontmatter
- Contents
- Preface
- 1 Regression and the Normal Distribution
- Part I Linear Regression
- Part II Topics in Time Series
- Part III Topics in Nonlinear Regression
- Part IV Actuarial Applications
- 16 Frequency-Severity Models
- 17 Fat-Tailed Regression Models
- 18 Credibility and Bonus-Malus
- 19 Claims Triangles
- 20 Report Writing: Communicating Data Analysis Results
- 21 Designing Effective Graphs
- Brief Answers to Selected Exercises
- Appendix 1 Basic Statistical Inference
- Appendix 2 Matrix Algebra
- Appendix 3 Probability Tables
- Index
20 - Report Writing: Communicating Data Analysis Results
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- 1 Regression and the Normal Distribution
- Part I Linear Regression
- Part II Topics in Time Series
- Part III Topics in Nonlinear Regression
- Part IV Actuarial Applications
- 16 Frequency-Severity Models
- 17 Fat-Tailed Regression Models
- 18 Credibility and Bonus-Malus
- 19 Claims Triangles
- 20 Report Writing: Communicating Data Analysis Results
- 21 Designing Effective Graphs
- Brief Answers to Selected Exercises
- Appendix 1 Basic Statistical Inference
- Appendix 2 Matrix Algebra
- Appendix 3 Probability Tables
- Index
Summary
Chapter Preview. Statistical reports should be accessible to different types of readers. Such reports inform managers who desire broad overviews in nontechnical language and analysts who require technical details to replicate the study. This chapter summarizes methods of writing and organizing statistical reports. To illustrate, we will consider a report of claims from third-party automobile insurance.
Overview
The last relationship has been explored, the last parameter has been estimated, the last forecast has been made, and now you are ready to share the results of your statistical analysis with the world. The medium of communication can come in many forms: you may simply recommend to a client to “buy low, sell high” or you may give an oral presentation to your peers. Most likely, however, you will need to summarize your findings in a written report.
Communicating technical information is difficult for a variety of reasons. First, in most data analyses, there is no one “right” answer that the author is trying to communicate to the reader. To establish a right answer, one need only position the pros and cons of an issue and weigh their relative merits. In statistical reports, the author is trying to communicate data features and the relationship of the data to more general patterns, a much more complex task. Second, most reports written are directed at a primary client or audience. In contrast, statistical reports are often read by many different readers whose knowledge of statistical concepts varies extensively; it is important to take into consideration the characteristics of this heterogeneous readership when judging the pace and order in which the material is presented.
- Type
- Chapter
- Information
- Regression Modeling with Actuarial and Financial Applications , pp. 481 - 504Publisher: Cambridge University PressPrint publication year: 2009