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Decision Criteria¶
Two types of errors can be made when running a hypothesis test.
- Type I error. Occurs when we decide to reject a null hypothesis when it is true.
- Type II error. Occurs when we fail to reject a null hypothesis when it is false.
Decision criteria is the probability of committing a Type I error. It is also known as significance level or alpha level.
To state results from hypothesis tests, we need to compare the p-Value to the decision criteria.
- If p-Value is less than or equal to the decision criteria, we can reject the null hypothesis in favor of the alternative.
- If p-Value is greater than the decision criteria, we cannot reject the null hypothesis.
The default value for decision criteria is 0.05.