METHODS OF DATA ANALYSIS
PARAMETRIC AND NON PARAMETRIC TESTS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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This test is more powerful than the sign test because the sizes of the differences are totally ignored.
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True
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False
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Either A or B
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None of the above
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Explanation:
Detailed explanation-1: -The size of a test is the probability of incorrectly rejecting the null hypothesis if it is true. The power of a test is the probability of correctly rejecting the null hypothesis if it is false.
Detailed explanation-2: -A very important result, known as the Neyman Pearson Lemma, will reassure us that each of the tests we learned in Section 7 is the most powerful test for testing statistical hypotheses about the parameter under the assumed probability distribution.
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