Collect the sample data and compute the value of the test statistic

Collect the sample data and compute the value of the test statistic. In the trash bag case, we have computed the value of the test statistic to be z = 2.20.

Step 5: Calculate the p-value by using the test statistic value. The p-value for testing H0: μ = 50 versus Ha: μ > 50 in the trash bag case is the area under the standard normal curve to the right of the test statistic value z = 2.20. As illustrated in Figure 9.3(b), this area is 1 − .9861 = .0139. The p-value is the probability, computed assuming that H0: μ = 50 is true, of observing a value of the test statistic that is greater than or equal to the value z = 2.20 that we have actually computed from the sample data. The p-value of .0139 says that, if H0: μ = 50 is true, then only 139 in 10,000 of all possible test statistic values are at least as large, or extreme, as the value z = 2.20. That is, if we are to believe that H0 is true, we must believe that we have observed a test statistic value that can be described as a 139 in 10,000 chance. Because it is difficult to believe that we have observed a 139 in 10,000 chance, we intuitively have strong evidence that H0: μ = 50 is false and Ha: μ > 50 is true.

Figure 9.3: Testing H0: μ = 50 versus Ha: μ > 50 by Using Critical Values and the p-Value

Step 6: Reject H0 if the p-value is less than α. Recall that the television network has set α equal to .05. The p-value of .0139 is less than the α of .05. Comparing the two normal curves in Figures 9.3(a) and (b), we see that this implies that the test statistic value z = 2.20 is greater than the critical value z.05 = 1.645. Therefore, we can reject H0 by setting α equal to .05. As another example, suppose that the television network had set α equal to .01. The p-value of .0139 is greater than the α of .01. Comparing the two normal curves in Figures 9.3(b) and (c), we see that this implies that the test statistic value z = 2.20 is less than the critical value z.01 = 2.33. Therefore, we cannot reject H0 by setting α equal to .01. Generalizing these examples, we conclude that the value of the test statistic z will be greater than the critical value if and only if the p-value is less than α. That is, we can reject H0 in favor of Ha at level of significance α if and only if the p-value is less than α.

© NBC, Inc. Used with permission.

Note: This logo appears on an NBC advertising standards booklet. This booklet, along with other information provided by NBC and CBS, forms the basis for much of the discussion in the paragraph to the right.

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