Quote:
Originally Posted by abhishreshthaa Measuring the power of a Hypothesis Test  The measure of how well the test is working is called the power of the test.
 Type I error occurs when we reject Ho which is true and a (the significance level of the test) is the probability of making type  I error.
 Once the significance level is fixed, nothing can be done about a.
 Type II error occurs when we accept Ho which is false.
 The probability of type II error is b. The smaller the value of b, the better is the test. Alternately ( 1  b ) i.e. the probability of rejecting Ho when it is false should be as large as possible.
 Thus (1  b ) is the measure of the power of the test. If we plot the values of ( 1  b ) for each value of m f2 for which Ha is true, the resulting curve is known as a power curve.
 You can see from the figure given below that the power is simply ( 1  b ). In testing of a hypothesis high power is desirable.

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