In this web content, the author discusses the use of Bayes factors in testing hypotheses. The author presents a scenario where a minimum wage increase of $4 leads to a 1% increase in unemployment. The author explains that Bayes factors compare the data with both the null hypothesis and alternative hypotheses. They argue that Bayes factors can lead to accepting the null hypothesis even when the observed effect falls within the range predicted by the alternative hypothesis. The author also highlights the use of arbitrary default distributions in Bayes factors calculations. Overall, the author argues against the use of Bayes factors in research.
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