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In frequentist hypothesis testing, the $p$-value is the probability of a result as extreme (or more) than the observed result, under the assumption that the null hypothesis is true.

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How a two-tailed p-value is calculated for a two-sample t-test

I'm reading Discovering Knowledge in Data by Daniel T. Larose. In the two-sample t-test for difference in means section, there is the following example: tdata = x-bar(1) - (xbar2)/ sqrt(s^2(1)/n(1)+ …
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