Using COVID Vaccine Data to Teach Statistics
By LIDA TUNESI
Professor Frank Wang of LaGuardia Community College has developed a straightforward way of using data from COVID-19 vaccine trials to teach students about hypothesis testing.
But really, the benefits go both ways. Wang’s method uses the vaccine trials to help people understand a sometimes confusing topic, and it allows people who have learned only introductory statistics to interpret numbers that are key to ending the pandemic.
Wang’s work appears in the journal Numeracy.
Many students only take one semester of statistics, if they take it at all, Wang writes. This means they often don’t get to the two-sample hypothesis testing that would be a good fit for analyzing clinical trial results, but they do learn about one-sample models. So to give more people a chance to understand trial results and efficacy rates, he reframes trial data using the one-proportion z-Test.
Wang introduces the concepts of probability and the normal distribution, illustrated by a bell curve, via the simpler idea of flipping a coin. Then he explains that if you looked at a curve for the “null hypothesis” that a vaccine doesn’t work, you would see that Pfizer’s trial results are considered very unlikely. Essentially, this is a backwards way of saying it’s quite likely that the vaccine is, in fact, doing something.
Wang also notes the importance of sample size, meaning the fact that clinical trials need a certain number of volunteers before their results are meaningful and not just the result of happenstance.
With these ideas in place, Wang dives into explanations of the one-proportion z-Test and vaccine efficacy rates. He also includes a section on how you could use a two-sample test, for courses that get to that point.
“Students are regularly exposed to misinformation and disinformation,” Wang told LaGuardia. “By presenting the statistical requirements for drug approval by the Food and Drug Administration in a way that is understandable for community college students, I hope to empower students to differentiate truth from falsehood and make sound judgment.”