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Critical Thinking & COVID-19 XI: Fallacies of Generalization

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In the last essay we looked at the inductive generalization and its usefulness in reasoning about certain aspects of the pandemic. As with all reasoning, one must be careful to avoid mistakes in logic—what philosophers call fallacies. Three fallacies often arise from efforts to generalize. These are the hasty generalization, appeal to anecdotal evidence, and biased generalization. I will look at each of them in terms of the current pandemic. A hasty generalization occurs when a person draws a conclusion about a population based on a sample that is not large enough to adequately support the concussion. It has the following form:   Premise 1: Sample S (which is too small) is taken from population P. Premise 2: In Sample S X% of the observed A’s are B’s. Conclusion: X% of all A’s are B’s in Population P.   In the previous essay we saw a rough guide to sample sizes and looked at the margin of error and confidence level. In that context, the fallacy would occur when the sample was not large enough to warrant a person’s confidence in the conclusion. In the case of COVID-19 a generalization that is of great concern is drawing an inference about the lethality of the virus. The math for this is easy—the challenge is getting the right information. At this time, there are large samples of infected people—thousands of people have been tested around the world. As such, the inferences from these large samples to the lethality of the virus would not be a hasty generalization. But avoiding this fallacy does not mean that the generalization is a good one—there are other things that can go wrong. There are also inferences being drawn from relatively small samples, such as generalizations from various treatments being tested. For example, samples of people treated with hydroxychloroquine for COVID-19 are relatively small, so inferences from these samples to the whole population run the risk of committing a hasty generalization. This is not to deny that even small samples. . .

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News source: A Philosopher's Blog

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