Hypothesis Testing 2--Testing for Population Means In Hypothesis Testing 1, you were introduced to the ideas of hypothesis testing in the context of deciding whether a coin was fair or biased in favor ...

A type II error, also known as a false negative, is the miscalculation that occurs when a researcher accepts a false null hypothesis.

For decades, statistics students have learned about Type-I and Type-II Error in hypothesis testing. And they often get these terms confused. Let’s rename these ...

This said, “Type-I Error” and “Type-II Error” are clearly arbitrary labels! These names do not give the reader an intuitive sense of what you’re talking about!