Hypothesis Testing

Denoted by  $H_o$   , is a statement that there is no difference between a parameter and a specific value, or that there is no difference between two parameters.

This is a pre-determined error which the researcher is willing to risk in rejecting the null hypothesis when it is true.

This is the range of values of the test value that indicates that there is a significance difference and that the null hypothesis should be rejected.

It is denoted by  $H_1$   , is a statement that there is a difference between a parameter and a specific value, or that there is a difference between two parameters.

If the null hypothesis is true and accepted, or if it is false and rejected, the decision is correct. If the null hypothesis is true and rejected, the decision is incorrect.

This is the range of values of the test value that indicates that there is no significance difference and that the null hypothesis should be accepted.

If the null hypothesis is false and accepted, the decision is incorrect.

A type of test which indicates that the null hypothesis should be rejected when the test values is in the critical region on one side of the parameter.

It is a test with two rejection regions. In this test, the null hypothesis should be rejected when the test value is in either of the two critical regions.

It is a numerical value that states something about the entire population being studied.