Analysis 101, part 3: Sharing your findings

Catalogue number: 892000062020011

Release date: September 23, 2020

In this video, you will learn how to summarize and interpret your data and share your findings. The key elements to communicating your findings are as follows:

  • select your essential findings,
  • summarize and interpret the results,
  • organize and assess your reviews and
  • prepare for dissemination
Data journey step
Analyze, model
Data competency
Data analysis
Suggested prerequisites

Watch the video

Analysis 101, part 3: Sharing your findings - Transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Analysis 101, part 3: Sharing your findings")

Analysis 101: Part 3 - Sharing your findings

Hi, welcome to analysis 101 video 3. Now that we've learned how to plan an analytical project and perform, the analysis will discuss best practices for interpreting an sharing your findings.

Learning goals

In this video you will learn how to summarize an interpret your data and share your findings. The key elements to communicating your findings are as follows. Select your essential findings. Summarize an interpret the results. Organize an assess reviews. And prepare for dissemination.

Steps in the analytical process

(Diagram of 6 images representing the steps involved in the analyze phase of the data journey where the first steps represent the making of an analytical plan, the middle steps represent the implementation of said plan and the final steps are the sharing of your findings.)

Going back to our six analytical steps will focus on sharing our findings. If you've been watching the data literacy videos by Statistics Canada, you'll recognize that this work is part of the third step, which is the analyze phase of the data journey.

Step 5: Summarize and interpret your results

Let's start by discussing how to summarize an interpret your results.

Tell the story of your process

(Image of the 4 parts to for the 5th step: Context - Evidence from other countries or anecdotal; Methods - Comapre millennials (aged 25-34) to previous generations; Findings - Millennials have higher net worth and higher debt then Gen-X; Interpretation - Mortgages main contributor to debt for millennials.)

Presenting your findings clearly to others is one of the most challenging aspects of the analytical process. Let's use the millenial paper as an example. First we started with the context where we highlighted previous findings for American millennials, which motivated our study on Canadian millennials. Then we discussed our data and methodology defining millennials in explaining how we compared them with previous generations. Then we walked through the key findings. The storyline, for example, we explained that well, Millennials had higher net worth than generation X when they were younger. Millennials were also more indebted. Finally, we interpreted our findings, digging deeper into the Y. For millennials, we found that mortgage debt, which reflects higher housing values, contributed to their higher debt load.

Carefully select findings that are essential to your story

You'll likely produce several data tables or estimates throughout your analytical journey. Carefully select the findings that are essential to telling your story. Revisit your analytical questions an select visuals that clearly help to answer these questions. Remember that your results are not the story, but the evidence that supports your story.

Summarize your findings and present a logical storyline

Once you've selected the key results, summarize your findings and present them according to a logical storyline. Identify the key messages. Often these messages will serve as subheadings in a report or study. Also, always make sure to discuss your findings within the broader context of the topic. You've done great work and you want people to remember what your analysis contributes to the literature. Creating a clear storyline will ensure that people remember your work.

Define concepts

(Text on screen: A millennial is anyone in our dataset between 25 to 34 years old in 2016)

As you may recall from video to project specific definitions of key concepts may have been established before starting your analysis. It's worthwhile to include any relevant definitions in your written analysis, like our definition of Amillennial. This will help the audience better understand your findings.

Avoid jargon and explain abbreviations

In your written analysis, avoid jargon. An explain abbreviations clearly. For example, instead of using a statistical term such as synthetic birth cohort, explain your results in plain language. Define any acronyms that you use, like CSD, which stands for senses subdivision at the earliest possible opportunity.

Maintain neutrality

(Text on screen: Subjective - Large/small, High/Low, Only/A lot; Neutral - Rose or fell by X%, Higher or lower by X times.)

Ensure that you're maintaining neutrality by using plain language and not overstating your results, or speculating when interpreting them. Avoid qualifiers like large, high, or only, which can be subjective and focus on explaining things using neutral language.

(Text on screen: Subjective - Large/small, High/Low, Only/A lot; Neutral - Rose or fell by X%, Higher or lower by X times.)

Here are some examples that were not neutral and were improved by letting the data tell the story. Instead of employment growth plummeted down by 2%. You can say over the previous quarter employment fell 2%. The largest decline in the past two years. The second statement maintains neutrality. Instead of Millennials are dealing with a significantly worse housing market and have a lot more debt, you can say median mortgage debt from Millennials age 30 to 34 reached over 2.5 times their median after tax income. Don't rely on exaggerations to make your point stay neutral. These statements are robust and supported by the data.

Expect to make mistakes

Expect that you will make mistakes. It's a normal part of analytical work. Remember that you're the person most familiar with your project, which puts you in an ideal position to identify mistakes. When you complete your preliminary draft, leave it alone for a few days and review it with fresh eyes. Don't be afraid to ask others for help in correcting your errors, and remember that learning from your mistakes will strengthen your analytical skills.

Step 6: Disseminate your work

Next, we're going to review the last step. Which is how to prepare your work for dissemination and communicate your finding successfully.

Ask others to review your work

An important part of preparing your work for dissemination is asking others to review your work. You can request feedback from a range of people such as colleagues, managers, subject matter experts and data or methodology experts.

Seek feedback on different aspects of your work

Ask your reviewers for feedback on different aspects of your work, such as the clarity of your analytical objectives, appropriateness of the data you've used, definition of concepts, review of literature, methodological approach, interpretation of your results and clarity and neutrality of your writing.

Organize and assess reviewers' comments

After receiving comments from your reviewers, organize and assess their feedback. Look for any concerns that are common across reviewers comments and determine which concerns will require additional analysis. Make sure to clarify anything that reviewers struggled to understand.

Document how you addressed reviewers' comments

Document how you've addressed each of the reviewers comments. If you're not able to address certain concerns, it's important to justify why. In some cases, your organization may require that you provide a formal response to reviewers comments. However, even if this is not required, it is a best practice to make note of the decisions you make when revising your work.

Preparing your work for publication involves many people and processes

Typically many processes and many people are involved in helping to prepare your analytical product for dissemination. At Statistics Canada, analytical products undergo editing, formatting, translation, Accessibility, assessment approval processes, and the preparation of a press release. You will want to consider their requirements for your work, whether it's a briefing note, an infographic or information on your organization's website.

How your work is published depends on your intended audience

How you work is disseminated will depend on your intended audience. You need to think about who the intended audience is. What do they already know? And what do they need to know for example the general public will want high level key messages while the media or policy analyst community will want more information visuals and charts. Researchers, academics, or experts will want details about your data, methodology and limitations of your work.

How your work is published depends on your intended audience: Media and the general public

For example, we often provide highlights visually through charts and infographics when communicating findings to the general public. For a study on the economic well being of millennials, the findings were communicated through Twitter, an infographic and a press release which summarized the key messages of the analysis.

How your work is published depends on your intended audience: Policy-makers

Other audiences such as policy makers may be interested in more detailed findings or a different venue where they can have their questions answered quickly. Results from the millenial study were shared with analysts and policy makers through a web and R the publication of a study with detailed results and other presentations.

How your work is published depends on your intended audience: Researchers, academics, experts

Findings are shared with researchers, academics or experts by publishing the analysis in detailed research papers or Journal articles in peer reviewed publications, as well as by presenting at conferences. This audience will be more invested in the specific details of. Work and knowing where the findings fit into the larger research field and knowledge base.

Communicating your work to the media requires preparation

Lastly, preparation is essential to successfully communicate your work to the media. Check to see if your organization offers media training. Prior to sharing your findings with the media, devote time to summarizing your main results and determining your key messages. Think about how to communicate your findings in simple terms. Anticipate potential questions and create a mock question and answer document.

Summary of key points

And that's a quick description of how to review and disseminate your work. First, tell the story of your process. Second, interpret your findings using clear an neutral language. 3rd, ask others to review your work and forth. Preparation is key to communicating your findings. Remember to always stay true to your analytical question while telling a clear story. Next, take a look at our case study, where we provide an example of the analytical process through the lens of a study about neighborhood walkability and physical activity.

(The Canada Wordmark appears.)

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