Hypothesis Testing Errors and Concepts

Analyzing regression models

Discussing data collection methods

Explaining Type 1 and Type 2 errors

Understanding statistical significance

To prove the null hypothesis

To collect more data

To determine the truth of the null hypothesis

To make a decision about the null hypothesis

Correctly rejecting a false null hypothesis

Rejecting a true null hypothesis

Correctly accepting a true null hypothesis

Failing to reject a false null hypothesis

Rejecting a true null hypothesis

Failing to reject a false null hypothesis

Correctly rejecting a false null hypothesis

Correctly accepting a true null hypothesis

By checking if the null hypothesis was correctly rejected

By checking if the null hypothesis was accepted when false

By checking if the null hypothesis was rejected when true

By checking if the null hypothesis was not rejected

The null hypothesis is correctly rejected

The null hypothesis is incorrectly accepted

An effect is missed when it exists

An effect is detected when there is none

Missing an effect that is present

Ignoring an effect that is present

Detecting an effect that is not present

Correctly identifying an effect

Failing to warn about a severe event

Issuing a warning for a non-severe event

Ignoring a non-severe event

Correctly predicting a severe event

To avoid unnecessary panic

To ensure warnings are always heeded

To save resources

To prevent loss of life

Ignoring a non-severe event

Correctly predicting a non-severe event

Failing to warn about a severe event

Issuing an unnecessary warning