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Unformatted text preview: Section 6.3 Using Significance Tests Section 6.3 1 Introduction Significance tests are widely used in reporting the results of research in many fields of applied science and in industry. Statistical significance is valued because it points to a result that is unlikely to occur simply by chance alone. Software makes the computation of test statistics and pvalues straightforward. Applying tests appropriately can be challenging. Section 6.3 2 What is a convincing pvalue? The purpose of a significance test is to describe the evidence that the sample provides against the null hypothesis. The pvalue is a quantitative measure of this evidence. How small should the pvalue be to be considered convincing evidence? One option is to use our fixed level of significance , but this is somewhat arbitrary. Section 6.3 3 Considerations for pvalues Some considerations in assessing pvalues: How plausible is H ? If H represents a longstanding belief, strong evidence (a small pvalue ) will be needed to persuade the audience. What are the consequences of rejecting H ? If rejecting H in favor of H A requires expensive adjustments, strong evidence will be needed to justify the expense. Would even small amounts of evidence be useful? Often in pilot studies or multivariable studies, modest pvalues will give clues about variables or relationships that should be investigated more thoroughly. Section 6.3 4 Reporting pvalues Recall that the choice of significance level is arbitrary. Traditional standard levels have included 1%, 5% and 10%....
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 Spring '08
 ABBEY
 PValues

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