In the Fall of 2020, my colleague, Prof. Immaculata De Vivo of the Harvard School of Public Health, and I wrote an essay about the public perception of risk and uncertainty, especially with regard to COVID-19. In this post, we are gathering comments from students in the Spring 2021 edition of "GenEd 1112: The Past and Present of the Future," an undergraduate course I teach at Harvard. Students were asked to read the essay, and then comment here on which part(s) of the discussion they expect would be most illuminating for non-quantitatively-inclined readers --and/or to suggest another framing of the issues discussed that would be more effective.
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I would assume the most challenging aspect of the article for students unfamiliar with quantitative prediction in general is likely the section discussing the detailed calculations of risk and uncertainty related to COVID-19. Here, the article introduces concepts like fractions, percentages, and the factors affecting these calculations, such as numerator, denominator, and uncertainty range. This involves mathematical reasoning and understanding statistical measures that can be quite complex for those not comfortable in quantitative methods. Understanding how these calculations relate to real-world risk assessment, particularly in a public health context, requires a grasp of both statistical concepts and their application to everyday decisions and policy-making.