Examlex
How is development measured? Why do we use more than one indicator?
Type I Error
A statistical error made by rejecting the null hypothesis when it is actually true, known as a false positive.
Type II Error
The failure to reject a false null hypothesis, also known as a "false negative."
Null Hypothesis
A statement positing that there is no significant difference or effect, serving as the default assumption in hypothesis testing.
Type II Error
The error that occurs when a false null hypothesis is not rejected, also known as a "false negative."
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