How do you calculate the p-value in hypothesis testing and what does it represent in the context of making a statistical decision?

The p-value in hypothesis testing is calculated using statistical tests like t-tests, chi-square tests, or ANOVA. It represents the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. A smaller p-value indicates stronger evidence against the null hypothesis, guiding the decision to reject or fail to reject it.

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