Dangerous Numbers? Teaching About Data and Statistics Using the Coronavirus Outbreak

Dangerous Numbers? Teaching About Data and Statistics Using the Coronavirus Outbreak

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Featured Article: “We’re Reading the Coronavirus Numbers Wrong” by John Allen Paulos

In his recent New York Times Opinion piece, John Allen Paulos, a professor of mathematics, cautions about the way in which we interpret and report disease-related data. In this lesson, you will see what numbers and statistics can tell us about disease outbreaks and how that data can be misinterpreted. Then you will analyze other examples of data reporting in the news and determine how accurate or effective it is.

Respond to the following questions in writing, or engage in a class discussion:

  • What have you heard about the coronavirus? Do you talk about it at school or with friends or family?

  • How do you see coronavirus discussed in the news or on social media? Have you seen memes or TikTok videos about the coronavirus? What tone do these sources take?

  • How concerned are you about the coronavirus? What has influenced how you think and feel about global outbreak?

(Feel free to join our related Student Opinion conversation about these topics. Commenting is easy — it only takes seconds to register, and it’s free — but you must be 13 or older to participate.)

Read the article, then answer the following questions:

1. How can you calculate the case fatality rate for a disease? What are the challenges to determining an accurate coronavirus fatality rate?

2. How do the changing coronavirus numbers in Hubei, China, illustrate how numbers can provide a distorted picture of what is going on?

3. What role does the media play in our understanding of the coronavirus outbreak? Why does Mr. Paulos say, “Constant on-the-nose reporting, however much it seems to serve transparency, has limitations, too.” What do you think? What are the advantages and disadvantages to the 24-hour news cycle?

4. How does the case fatality rate of Covid-19 compare with that of other diseases, based on what we know now? How might the numbers tell a different story as we gather additional data over the next weeks or months?

5. What are some of Mr. Paulos’s suggested remedies?

Teachers: The featured Op-Ed essay creates an opportunity to actively engage with how data is presented and reported. In this activity, encourage students to analyze data and see if they can find other examples of “dangerous numbers.”

Have students search The Times and other news outlets for articles that focus on data. Students could choose to look further at the latest updates on the coronavirus. Or they can search poll numbers for the Democratic primaries, climate change statistics or unemployment data. With an eye on the numbers, students can identify potential misrepresentations and misinterpretations of data, and maybe spot a “numerical optical illusion” of their own.

Here are some questions that can help frame their analysis:

Numbers may seem fixed and unambiguous, but as Mr. Paulos points out, even a seemingly straightforward data point like “number of deaths” can be vague:

The coronavirus might be blamed for the deaths of vulnerable people, especially seniors, already suffering from other illnesses, such as diabetes and other chronic conditions.

Real World Example: Unemployment may seem like a clear concept: People either have a job or they don’t. However, what if a person works only a few months out of the year? Or what if they work multiple part-time jobs at once?

Ask Yourself: Do I really understand the nature of the data? Find out where the data comes from and what it actually represents. Then consider how different interpretations of that data could lead to different conclusions.

When quantities rise and fall, medical officials and news outlets often create a narrative around why that happened; however, those narratives are not always accurate. For example, when looking at the increase in reported cases of coronavirus, Mr. Paulos explains that it could be because the virus is spreading, but it could also be a result of the revised definition of what it means to be “infected” with the coronavirus.

Real World Example: When stock prices rise and fall, there is no shortage of explanations for why it happened. However, it is important to ask if the company’s stock price fell because of a C.E.O.’s poor decision, or because the company just had a bad week?

Ask Yourself: Who benefits from interpreting the numbers in this way? What perspective or bias might they have? For example, is there a reason that one candidate is “surging” when polling at 13 percent, while another is “struggling” with the same numbers? Every story has a narrator, and you want to identify who the narrator is and why he or she is telling the story in a particular way.

There is always more data, so look for related reporting to see what else there is to know. For example, local polling data can be compared with national polling data. And industry averages can help put individual business numbers in perspective, while looking at transportation and travel data can help us understand how outbreaks might be spreading.

Ask Yourself: What else is there to know? Where can I find more data on this subject? This question is particularly helpful to ask when you are trying to paint a picture using data.

Teachers: If there is time, students can present a summary of their findings, including an analysis of how the data was used and interpreted. They can also share whether they think they found any “dangerous numbers.” Student can also offer suggestions on how to improve the reporting and interpretation of the data.