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Type I and Type II errors

In statistical hypothesis testing, Type I and Type II errors are concepts that help researchers understand the risks associated with decision-making. A Type I error (false positive) occurs when the null hypothesis is incorrectly rejected, meaning the researcher concludes there is an effect when none actually exists. Conversely, a Type II error (false negative) happens when the null hypothesis is not rejected despite...

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