Type I and Type II error

Let alpha denote the probability of Type I error let beta denote the probability of a Type II error

Then alpha is called the size (or significance level) of the test, and 1 minus beta is called the power of the test.

The size and power of a test can be used to decide whether or not the test is a good test.

$$1 - \beta$$ is called the power of the test.

The size and power of a test can be used to decide whether or not the test is a good test.

Type II Error
in general the sum of \alpha and \beta should be less than 1, and in order for the test to be useful much less than 1