How to Write Data Analysis Reports in Six Easy Lessons

There’s a lot to consider but it’s not overwhelming when you break it down into small chunks.

Charlie Kufs
Aug 27 · 18 min read

This article is an abridged version of a longer blog, also available as a PDF. This article includes the key ideas of the original blogs without the twenty graphics and intense formatting that would cause Medium’s online editor to self-destruct. You’ll get the idea of what I’m saying and you can follow the links if you want more.

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Writing Data Analysis Reports

In every data analysis, putting the analysis and the results into a comprehensible report is the final, and for some analysts, the biggest hurdle. For many readers, the technical information in a data analysis report is difficult to understand because it is complicated and not readily understood. Add math anxiety and the all too prevalent notion that anything can be proven with statistics and you can understand why reporting on a data analysis is a challenge.

It’s not uncommon for data scientists to receive little or no effective training in good technical writing. The ability to write effective reports is not the same as writing a report for a class project that only the instructor will read. Some data scientists have never done it and may even fear the process. Some may think that every report is pretty much the same. Some learned under different conditions, like writing company newsletters or personal blogs, and figure they know as much as they need to know about it. And worst of all, some have done it without guidance and have developed bad habits, but don’t know it.

It’s a pretty safe bet that you’ll benefit from learning about writing technical reports. Four things you can do to improve your skills.

  • Educate yourself. Learn what other people think about technical writing. Visit websites on “statistical analysis reports” and “technical writing,” there are millions of them. Take online or local classes. Read books and manuals. Join Internet groups, such as through Google or LinkedIn. Immerse yourself in the topic as you did when you were in school.
  • Understand criticism. Over the course of your career, you’ll give and receive a lot of criticism on technical reports. Not all criticism is created equal. First, consider the source. Some critics have never written a report on a data analysis and some have never even analyzed data. Still, if the critic is the one paying the bills you have to deal with it. For your part, you should learn how to provide constructive criticism. Unless a report you are reviewing is a complete mess, respect the report writer’s discretion for structure and format. Focus on content. Be nice.
  • Download examples. Search the internet for examples of data analysis reports (Hint: adding pdf and download to the search might help). Critique them. Who’s the audience? What’s the message? What’s good and bad about each report? Which reports do you think are good examples? What do they do that you might want to do yourself in the future?
  • Find what’s right for you. When you search the Internet for advice on technical writing or take a few classes from knowledgeable instructors, you’ll hear some different opinions. Everyone will talk about audience and content but most will have more limited views of report organization, writing style, and how you work at writing. Ignore what the experts tell you to do if it doesn’t feel right. Just be sure that the path you eventually choose works for you and the audiences who will read your reports.

Consider these six easy lessons:

Lesson 1 — Know your Content

Start with what you know best. In writing a data analysis report, what you know best would be the statistics, graphing, and modeling you did.

From that, you’ll need to determine what’s important, and then, what’s important to the reader. Unless you’re writing the report to your Professor in college or your peers in a group of professional data analysts, you can be pretty sure that no one will want to hear about all the issues you had to deal with, the techniques you used, or how hard you worked on the analysis. No one will care if your results came from Excel or an R program you wrote. They’ll just want to hear your conclusions.

The message you want to deliver is the most important thing you’ll have to keep in mind while writing. Write an overview to the report to help you stay on track. Your summary might take one of three forms:

  • Executive Summary. Aimed at decision makers and people with not enough time or patience to read more than 400 words. Limit your summary to less than one-page, do not use any jargon, and provide only the result the decision maker needs to know to take an appropriate action (i.e., the message you want to convey).
  • Overview. Aimed at most people, whether they would read the report or not. An overview is an abridged version of what is in the report, with a focus on the message you want to convey. The overview shouldn’t be more than a few pages.
  • Abstract. Aimed at peers and other people who understand data analysis. An abstract summarizes in a page or less everything of importance that you did, from defining the population through assessing effect sizes. Abstracts are most often used in academic articles.

Once you understand who your audience is, you can rewrite the summary to catch the attention of your readers.

Lesson 2 — Know Your Audience

Every self-help article about technical writing starts by telling readers to consider their audience. Not enough writers do.

In a statistical analysis, you usually start by considering the characteristics of the population about which you want to make inferences. Similarly, when you begin to write a report on an analysis, you usually start by considering the characteristics of the audience with which you want to communicate. You have to think about the who, what, why, where, when, and how of the key people who will be reading your report.


Audience is often defined by the role a reader plays relative to the report. Audiences for a statistical report may be defined as decision-makers, stakeholders, reviewers, or generally-interested-individuals. There can be primary, secondary, and even more levels of audience participation. This is problematical; you can’t please everyone. So, in defining your audience, focus first on the most important people to receive your message and second on the largest group of people in the audience.


Once you define who you are targeting with your report, you should try to understand their characteristics. Perhaps the most important audience characteristic is their understanding of the subject matter and the analysis being described. You won’t be able to do much about their knowledge but you can adjust how you present your work. You may encounter:

  • Mathphobes. Fear numbers but may listen to concepts. Don’t use any statistical jargon. Don’t show formulas. Use numbers sparingly. For example, substitute “about half” for any percentage around 50%. The extra precision won’t be important to a Mathphobe.
  • Bypassers. Understand some but have little interest. Don’t worry about Bypassers, they won’t read past the summary. Be sure to make the summary pithy and highlight the most important finding otherwise they might key on something relatively inconsequential. Those misleading internet articles about scientific research were written by bypassers.
  • Tourists. Understand some and are interested. Be gentle. Use only essential jargon that you define clearly. Using numbers is fine just don’t use too many in a single table. Round off values so you’re not implying false precision. Stick with nothing more sophisticated than pie charts, bar graphs, and maybe an occasional scatter chart. Don’t use any formulas.
  • Hot Dogs. Know less than they think and want to show it. Dunning-Kruger people. Using jargon is fine so long as you define what you mean. Even a Hot Dog may learn something. In the same vein, using numbers, statistical graphics, and formulas is fine so long as you clearly explain their meanings. Hot Dogs may come to erroneous conclusions if not guided.
  • Associates. Other analysts who understand the basic jargon. Anything is fine so long as you clearly explain what you mean.
  • Peers. Other data analysts who understand all the jargon. Anything goes.

The audience characteristics provide guidance for report length and writing tone and style


What is the objective of the who you defined as your audience? What will they do with your findings? Is this a big thing for them or just something they have to tune in to?


Is the report aimed at a finite, confined group, like the organization the analysis was conducted for, or will anyone be able to read it? Is the report aimed at the upper levels of the organization or the rank-and-file (i.e., bottom up or top down)? Are there any concerns for security or confidentiality, either on the individual or organizational levels?


When does the population need to see your report? Who has to review the report and how long might they take before the report is released? How firm are the deadlines? How much time does this leave you to write the report?

Here’s some advice you should take to heart. Never, never, never submit a draft report for review that isn’t your fully complete, edited, masterpiece. I told myself to follow this rule with every report I wrote. Unfortunately, like most people, I didn’t listen and paid the price more than once.


Finally, consider how the report should be presented so that the audience will get the most out of it. Here are five considerations:

  • Package. How will your writing be packaged (i.e., assembled into a product for distribution)? Will it be a short letter report, a comprehensive report, a blog or an Internet article, a professional journal article, a white-paper, or will your writing be included as part of another document?
  • Format. Will your report be distributed as an electronic file of as a paper document? If it will be an electronic document, will it be available on the Internet? Will it be editable? Will it be restricted somehow, such as with a password?
  • Appearance. Will the report be limited to black-and-white or will color be included? What will be the ratio of graphics to text? Will the report be conventional or glitzy, like a marketing brochure? Will there be 11”x17” foldout pages or oversized inserts like maps.
  • Specialty items. Will you need to provide some items apart from the report, such as electronic data files, analysis scripts or program codes, and computer outputs? Will you have to create a presentation from the contents of the report? Will your graphics be used for courtroom or public presentations?
  • Accessibility. Do you need to follow the guidelines of Section 508 of the Rehabilitation Act of 1973, which may affect your use of headings, tables, graphic objects, and special characters? Should you account for common forms of color blindness in your color graphics? Do your pictures have to be licensed?

You won’t have to address all of these details in evaluating your audience and many will only require a few moments of thought. But, if you think through these considerations, you’ll have a much better idea of who you are writing the report for and how you should write it.

Lesson 3 — Know Your Route

You’ve been taught since high school to start with an outline. Nothing has changed with that. However, there are many possible outlines you can follow depending on your audience and what they expect. The first thing you have to decide is what the packaged report will look like.

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Just as there are several possible routes you could take with a map, there are several possible outline strategies you could use to write your report. Here are six.

  • The Whatever-Feels-Right Approach. This is what inexperienced report writers do when they have no guidelines. They do what they might have done in college or just make it up as they go along. This might work out just fine or be as confusing as The Maury Show on Father’s Day. Considering that the report involves statistics, you can guess which it would be.
  • The Historical Approach. This is another approach that inexperienced report writers use. They do what was done the last time a similar report was produced. This also might work out fine. Then again, the last report may have been a failure, ineffective in communicating its message.
  • The “Standard” Approach. Sometimes companies or organizations have standard guidelines for all their reports, even requiring the completion of a formal review process before the report is released. Many academic and professional journals use such a prescriptive approach. The results may or may not be good, but at least they look like all the other reports.
  • The Military Approach. You tell ’em what you’re going to tell ’em, you tell ’em, and then you tell ’em what you told ’em. The military approach may be redundant and boring, but some professions live by it. It works well if you have a critical message that can get lost in details.
  • The Follow-the-Data Approach. If you have a very structured data analysis it can be advantageous to report on each piece of data in sequence. Surveys often fall into this category. This approach makes it easy to write the report because sections can be segregated and doled out to other people to write, before being reassembled in the original order. The disadvantage is that there usually is no overall synthesis of the results. Readers are left on their own to figure out what it all means.
  • The Tell-a-Story Approach. This approach assumes that reading a statistical report shouldn’t be as monotonous as mowing the lawn. Instead, you should pique the reader’s curiosity by exposing the findings like a murder mystery, piece by piece, so that everything fits together when you announce the conclusion. This is almost the opposite of the follow-the-data approach. In the tell-a-story approach, the report starts with the simplest data analyses and builds, section by section, to the great climax — the message of the analysis. Analyses that are not relevant to the message are omitted. There are usually arcs, in which a previously introduced analytical result is reiterated in subsequent sections to show how it supports the story line. Graphics are critical in this approach; outlines are more like storyboards. There may be the equivalent of one page of graphics for every page of text. Telling a story usually takes longer to write than the other approaches but the results are more memorable if your audience has the patience to read everything (i.e., don’t try to tell a story to a Bypasser.)

So, be sure that you have an appropriate outline but don’t let it constrain you. Having a map doesn’t mean you can’t change your route along the way, you just need to get to the destination.

Lesson 4 — Get Their Attention

If you’re writing a data-analysis report, you have to expect that many readers will lose interest after a while, maybe like fifteen seconds, if they even had it to begin with. So, in writing the report, think about how you might engage your audience. Here are five ideas.

  • Find Common Ground. Every relationship begins with having something in common. Fighting a common foe or solving a common problem can form the strongest and longest lasting of bonds. So the first thing you should try to establish in your report is that common ground. This isn’t so difficult if you are working on an analysis at the behest of a client. The client is already immersed in the data and has invested in you to help solve the problem. Establishing common ground is not so easy if you are proffering an uninvited message. Some people, perhaps subconsciously, don’t really want the message you are offering, especially when you’re analyzing data in their area of expertise. Try to establish common ground in other areas. Perhaps your analysis touches on a similar or analogous issue the reader might have. Maybe the analysis procedure could be used on a different problem the reader might have.
  • Clear the Decks. Get rid of everything that doesn’t add to the progression of the report. That doesn’t necessarily mean you have to omit the content. You can relegate it to an appendix, which is pretty much the same thing. Unless required to be in the body of the report, things like the data, data collection surveys and forms, and scrubbing and analysis procedures should all be put in an appendix.
  • Set the Tone. Your writing style can either add to or detract from the readability of your report. A formal tone, with strict adherence to grammar rules, complex sentence structures, use of third-person point-of-view and passive voice, and plentiful jargon, is typical of most data analysis reports. Formal tones are good for describing details, specifications, and step-by-step instructions. However, formal tones can be more difficult to understand, especially for individuals not accustomed to reading technical reports. An informal tone, with simple grammar and vocabulary, colloquialisms, contractions, analogies, and humor, works well for blogs. Informal tones are good for discussing ideas and concepts, and for inspiring readers or communicating a vision. They are more engaging and tend to be easier for most individuals to understand. If you’re being paid to write the report, a formal tone is usually more appropriate. This is problematical, of course, because formal writing is usually harder to read and maintain an interest in.
  • Add Mind Candy. A Harry Potter novel consisting of page-after-page of text will keep readers, young and old, transfixed for hours. A data analysis report consisting of page-after-page of text will put readers into a coma faster than taking a handful of barbiturates with a glass of warm milk while meditating in a tub of hot water. The difference is that the novel engages readers with mental images. Data analysis reports need to use visual imagery, which for the most part means good graphics. Granted, most readers won’t understand anything more complicated than a pie chart or a bar chart, but don’t add to the confusion. Three-dimensions are a no-no. Avoid graphing data in more than a few categories to avoid making the slices and bars so thin as to be uninterpretable. And most importantly, make sure they add to the analysis. You can do more, too. Break up the text with subheadings and bullets. Reiterate information nuggets in boxes instead of just letting them get lost in the text. Use tables for explaining differences in data groups and not just for number buckets. Add footnotes or hyperlinks to explain collateral concepts.
  • Make it Better. Just when you think you’re done writing, you’re not. That’s the time when you have to do even more to make the report better. First, take some time off if you can. Then, read it through again making improvements along the way. Read it aloud if you need to, even record it when you read it aloud and then play it back so you can engage both your vision and hearing. Consider getting a second opinion, especially if you can’t distance yourself from the report by setting it aside for a few days. A second opinion may come from a data analysis peer, but don’t ignore nontechnical editors. A good editor can help with spelling, grammar, punctuation, word choice, style and tone, formatting, references, and accessibility. It’s usually worth the effort. This is the time to go for purrfection.
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Lesson 5 — Get It Done

Perhaps the hardest part of writing a data analysis report is just getting it completed. Writer’s block is an impediment experienced by all writers. Writer’s block might be attributable to not knowing what to write next, trying to write text that is perfect, or fear of failure. Any of these reasons may be applicable to the report writer. Here are ten ways to fight off writer’s block.

1. Stick with a routine. Keep writing even if you are dissatisfied with what you’ve written. You can, and should, edit your draft after you’re done. Try to identify your productivity tipping point. For some people, accomplishing a specific goal by a certain time in a day helps ensure the rest of your day is productive. For example, my productivity tipping point is beginning to write by 8AM. If I do, I’ll be writing productively all day.

2. Visualize. If you’ve never used visualization techniques before, now is a good time to develop the skill. The idea is to close your eyes, get relaxed, and think about what you want to do or see. Start by visualizing what the next few sentences you have to write might look and sound like. Eventually, you’ll be able to visualize what paragraphs, sections, and even the entire final product will look like.

3. Eschew perfection. If it’s not perfect the first time you write it, leave it alone. Let it age while you write the rest of the report. You can reevaluate and rewrite it later when you know more about the rest of the report. (This is why you should never release a draft that you don’t feel is your best and final effort.)

4. Write in parallel. Some parts of reports, like introductions and summaries, and descriptions of variables and other details, are almost formulaic. Write all the similar parts at the same time. Set up a second file in your word processing software to serve as a staging area for the repeated parts. Then, copy and paste the standardized parts to your report and edit the text as appropriate.

5. Grow the outline. Instead of trying to write the report section by section, try using the outline as a template rather than a map. Add key phrases, instructions, notes, sentences, and even paragraphs to the template-outline. You can skip around the template-outline as you come up with ideas for what to write. Eventually, you can consolidate these ideas into paragraphs and then sections. Continue to expand the template-outline until it ultimately becomes the complete report.

6. Tiptoe through the tables. Create all or most of your graphics (i.e., tables and figures) before starting to write. Lay the graphics out in your word processing software and write the text that would go with each graphic. Then, go back and fill in the gaps between graphics. Continue joining the pieces until the report is complete.

7. Chunk it up. Don’t try to write the entire report by yourself. Break it up into pieces and get help.

8. Set deadlines. Sometimes it helps to be able to work towards an interim goal. Set deadlines for sections or other tasks you have to accomplish. Make them challenging but achievable. The deadline doesn’t have to be a calendar date a month away. Sometimes, the best deadlines are for small accomplishments, like finishing a paragraph before eating that Snickers bar.

9. Give it a rest. Absence makes the mind grow sharper. Consider taking some time off from report writing, but make sure you use the time productively. Schedule that colonoscopy you’ve been putting off. Clean the garage and paint the house. Visit your in-laws. Don’t just play video games or watch Netflix.

10. Do something different. If your routine isn’t working, try doing something different. If you can’t get anywhere because you’re pressing, work on something else or take some time off. If you can’t get anywhere because you’re slacking, try researching. If you can’t get anywhere because you’re stuck on writing, pull together graphics or the appendices. If you can’t get anywhere because you’re procrastinating, ask yourself why.

Lesson 6 — Get Acceptance

Data analysis reports have to go through one more hurdle after they are completely written. They have to be approved for acceptance by a gatekeeper. The approval for acceptance may involve allowing report distribution, starting the publishing process, issuing payment for your services, or just acknowledging that your work is done. The gatekeeper may be your client, your supervisor, your publisher, or for blog writers, you.

To get that approval, formal reports usually have to be reviewed by reviewers. Reviewers are usually individuals the gatekeeper chooses based on their technical background or role in the gatekeeper’s organization. Sometimes, reviewers are individuals the gatekeeper is forced to listen to, like regulatory reviewers. In academic publishing, you may not even know who the peer reviewers are. Be prepared, reviews can far longer than report preparation.

The number of comments you get from the reviewers is inconsequential. Great reports can get dozens of highly critical comments. The only review you should be concerned about is the one that provides no comments. That usually signals a lack of interest by the reviewers and the gatekeeper. If this is the case, your report will never leave the shelf.

If you’ve written an informal piece, like a blog, you are the gatekeeper, but you may still get comments. That’s good because it shows that people are reading your blog. Unfortunately, some of the comments may come from spammers, trolls, 13-year-olds, head cases, angry arguers, and other individuals who won’t be providing constructive criticism. First, consider the source of each comment. You may not have to respond to some of them. Beware, sometimes malicious commenters use addresses that link to spam or malware.

Don’t get upset by reviewers pointing out flaws in your report. That’s what they’re supposed to do. Having been on both sides of the writer/reviewer divide, I can tell you that creating a report takes a hundred times more knowledge, creativity, effort, and time than reviewing a report. Providing constructive criticism on a report requires a hundred times more experience, situational awareness, and interpersonal sensitivity than creating a report. Good writing combined with constructive reviewing makes a data analysis report the best it can be.

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Stats with Cats

… for when you can’t solve life’s problems with statistics alone.

Charlie Kufs

Written by

I’ve analyzed data for over 40 years, written a book and over 150 blogs, been a trainer/public speaker, and was a PG and SSGB. Now retired, I worship cats.

Stats with Cats

Stats With Cats is for people who want to learn basic statistics. You won’t find a lot of equations or higher math. You will find articles about the skills you’ll need to complete your own statistical analyses — data scrubbing, variance, models, and report writing.

Charlie Kufs

Written by

I’ve analyzed data for over 40 years, written a book and over 150 blogs, been a trainer/public speaker, and was a PG and SSGB. Now retired, I worship cats.

Stats with Cats

Stats With Cats is for people who want to learn basic statistics. You won’t find a lot of equations or higher math. You will find articles about the skills you’ll need to complete your own statistical analyses — data scrubbing, variance, models, and report writing.

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