Essential Statistics

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Chapter 12: Hypothesis Tests – Large Samples 579
We used the P-value to measure the strength of the evidence against the null
hypothesis for that test. The smaller the P-value, the stronger will be the
evidence against the null hypothesis. That is, the smaller the P-value, the
stronger is the evidence that we should reject the null hypothesis in favor of
the alternative hypothesis.
We may further fine tune the range of the P-values to quantify the strength
of the evidence against the null hypothesis.
Typical, or a Rule-of-Thumb cutoff points, are given next.
 P-value > 0.1  little evidence against
 0.05 < P-value  0.1  some evidence against
 0.01 < P-value  0.05  moderate evidence against
 0.001 < P-value  0.01  strong evidence against
 P-value  0.001  very strong evidence against
Using the above guide to make a decision, for Examples 12.13, we will
reject the null hypothesis since the P-value = 0.0097 which is smaller than
the significance level  = 5% = 0.05. Based on the Rule-of-Thumb, a
P -value of 0.0097, would suggest that the evidence against the null
hypothesis is moderate
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