The process of hypothesis testing begins with the arrival of a sample statistic indicating that some action
needs to take place. The sample may indicate that:
1) the marketing director needs to do something because average sales are going down
2) the foreman needs to adjust something because parts may be too heavy to pass inspection
3) the auditor must test more accounts payable to prove the amount stated on the balance sheet
4) Our candidate is falling behind in the polls
We begin by accepting the conditions of the null hypothesis and that the results of our research will seldom
require action. When the test statistic is extreme enough to happen less than the level of significance, we
accept the alternate, research hypothesis. The marketing director calls a meeting to develop a plan to
increase average sales, the foreman makes an adjustment, tests more parts, or shuts down the assembly
line, the auditor samples another batch of payables, and the politician makes more speeches.
What do we do when the sample is not extreme enough to happen less than or equal to the level of
significance? Some people do not like to say we accept the null hypothesis because that indicates it is true
and we did not prove that it was true. We proved that it was not false. For this reason, many statistics books
fail to reject the null hypothesis rather than accept the null hypothesis.
See Dr. Wallace Hendricks',
University of Ill.
Syllabus for good Power Point
Hypothesis Testing presentations. See Chapter 8.
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