The sign test is a very simple procedure for testing hypotheses about a population median assuming only

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The sign test is a very simple procedure for testing hypotheses about a population median assuming only that the underlying distribution is continuous. To illustrate, consider the following sample of 20 observations on component lifetime (hr):

1.7 3.3 5.1 6.9 12.6 14.4 16.4 24.6 26.0 26.5 32.1 37.4 40.1 40.5 41.5 72.4 80.1 86.4 87.5 100.2 We wish to test versus . The test statistic is the number of observations that exceed 25.

a. Consider rejecting H0 if . What is the value of a

(the probability of a type I error) for this test? [Hint:

Think of a “success” as a lifetime that exceeds 25.0.

Then Y is the number of successes in the sample.] What kind of a distribution does Y have when ?

b. What rejection region of the form specifies a test with a significance level as close to .05 as possible? Use this region to carry out the test for the given data.

[Note: The test statistic is the number of differences that have positive signs, hence the name sign test.]

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