Applied Statistics
12. Statistical report writing
Learning to write useful, productive and readable statistical reports is a critical data analysis skill.
- Undergraduate Statistics Project
- Statistical Report Writing
- The book R eport Writing for Data Science in R by Roger D. Peng (freely dowloaded from LeanPub) is a useful reference for statistical report writing, especially when using the R programming language.
- The book C ommunicating with Data by Deborah Nolan and Sara Stoudt consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities
One model for a self-contained statistical report, especially one containing empirical methods, has the following sections:
- Give an informative title to your project.
- Assessment : Does the title give an accurate preview of what the report is about? Is it informative, specific and precise?
- The abstract provides a brief summary of the paper (background, methods, results and conclusions). The suggested length is no more than 150 words. This allows you approximately 1 sentence (and likely no more than 2 sentences) summarizing each of the following sections. Typically, abstracts are the last thing you write.
- Assessment : Are the main points of the report described clearly and succinctly?
- In this section you are providing the background of the report – the topic for analysis – and arguing its significance. Well-accepted facts or referenced statements should serve as the majority of content of this section. Typically, the background and significance section starts very broad and moves towards the specific area of analysis.
- Assessment :
Does the background and significance have a logical organization? Does it move from the general to the specific?
Has sufficient background been provided to understand the report?
Does this section end with statements about the goals of the report?
- Data collection . Explain how the data was collected/experiment was conducted.
- Variable creation . Detail the variables in your analysis and how they are defined (if necessary). For example, if you created a combined (frequency times quantity) drinking variable you should describe how. If you are talking about gender no further explanation is really needed.
- Analytic Methods . Explain the statistical procedures that will be used to analyze your data. E.g. Boxplots are used to illustrate differences in GPA across gender and class standing. Correlations are used to assess the impacts of gender and class standing on GPA.
- Assessment : Could the study be repeated based on the information given here? Is the material organized into logical categories (like those above)?
- Typically, results sections start with descriptive statistics, e.g. what percent of the sample is male/female, what is the mean GPA overall, in the different groups, etc. Figures can be nice to illustrate these differences! However, information presented must be relevant in helping to answer the research question(s) of interest. Typically, inferential (i.e. hypothesis tests) statistics come next. Tables can often be helpful for results from multiple regression. Do not give computer output here! This should look like a peer-reviewed journal article results section. Tables and figures should be labeled, embedded in the text, and referenced appropriately. The results section typically makes for fairly dry reading. It does not explain the impact of findings, it merely highlights and reports statistical information.
Is the content appropriate for a results section? Is there a clear description of the results?
Are the results/data analyzed well? Given the data in each figure/table is the interpretation accurate and logical? Is the analysis of the data thorough? Is anything relevant ignored?
Are the figures/tables appropriate for the data being discussed? Are the figure legends and titles clear and concise?
- Restate your objective and draw connections between your analyses and objective. In other words, how did (or didn’t) you answer/address your objective. Place these all in the larger scope of the relevant chapter of the text. Talk about the limitations of your findings and possible areas for future research to better investigate your research question. End with a concluding sentence or two that summarizes your key findings and impact on the field.
Do you clearly state whether the results answer any question posed?
Were specific data cited from the results to support each interpretation? Do you clearly articulate the basis for supporting or rejecting any hypotheses?
- You can copy & paste different style references from Google Scholar: here’s an example (click on the “Cite” link to see the different style citations).
- Assessment : Are references appropriate and of adequate quality? Are the cited properly (both in the text and at the end of the paper)?
Writing quality
- Is your report well-organized, with paragraphs organized in a logical manner?
- Is each paragraph well-written, with a clear topic sentence, and single major point?
- Is your report generally well-written, with good use of language, and sentence structure?
- Are tables and figures labeled correctly and referenced accordingly?
- Does the entire report flow and answer any question(s) sufficiently?
- Is there extraneous information presented (if so, delete it)?
Advice on writing statistical reports
Andrew Gelman
Andrew Gelman , Professor of Statistics and Political Science and Director of the Applied Statistics Center at Columbia University, wrote the following as a guide to preparing statistical research articles; it works equally well for writing statistical reports.
Please try to follow it, and see how your planning for writing for, and actual writing of, statistical reports improves:
- Start writing the conclusions (the final part of your report, before the references). Write up to a couple pages on what you’ve found and what you recommend. In writing these conclusions, you should also be writing some of the introduction, in that you’ll need to give enough background so that general readers can understand what you’re talking about and why they should care. But you want to start with the conclusions, because that will determine what sort of background information you’ll need to give.
- Now step back. What is the principal evidence for your conclusions? Make some graphs and pull out some key numbers that represent your research findings which back up your claims.
- Back one more step, now. What are the methods and data you used to obtain your findings?
- Now go back and write the literature review and the introduction .
- Moving forward one last time: go to your results and conclusions and give alternative explanations . Why might you be wrong? What are the limits of applicability of your findings? What future work would be appropriate to follow up on these loose ends?
- Write the abstract . An easy way to start is to take the first sentence from each of the first five paragraphs of the article. This probably won’t be quite right, but I bet it will be close to what you need.
- Give the article to a friend, ask them to spend 15 minutes looking at it, then ask what they think your message was, and what evidence you have for it. Your friend should read the article as a potential consumer, not as a critic. You can find typos on your own time, but you need somebody else’s eyes to get a sense of the message you’re sending.
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