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Which of the following is not true about p-values in hypothesis testing?

A) A smaller p-value indicates stronger evidence against the null hypothesis.
B) P-values are used to determine the size of the effect.
C) P-values are compared to a significance level.
D) P-values can be used to prove a hypothesis.

User TalesM
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Final answer:

P-values in hypothesis testing provide evidence for or against the null hypothesis, but cannot be used to prove a hypothesis.

Step-by-step explanation:

A) A smaller p-value indicates stronger evidence against the null hypothesis. B) P-values are used to determine the size of the effect. C) P-values are compared to a significance level. D) P-values can be used to prove a hypothesis.

The correct answer is D) P-values can be used to prove a hypothesis. In hypothesis testing, the purpose of the p-value is to assess the strength of the evidence against the null hypothesis. It provides a measure of how likely it is to observe the data or a more extreme result, given that the null hypothesis is true. However, p-values cannot be used to prove a hypothesis true or false; they can only provide evidence for or against the null hypothesis.

User Goldsmith
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