Question

When we use statistical software to compare the means with a significance test, we obtain the following printout: Variance T DF Prob>|T| Unequal 2.9146 41.9 0.006 1.3.1 Interpret the P-value, in context, based on its definition. (Note: You are not being asked to make a decision at some α-level.

Answer 1

The interpretation of the p-value is that there is a 0.006 = 0.6% probability of the sample means differing by the amount that they differed on the sample.

What are the hypothesis tested?

At the null hypothesis, it is tested if the means are equal, that is:

$H_0: \mu_1 = \mu_2$

At the alternative hypothesis, it is tested if the means are different, that is:

$H_1: \mu_1 \neq \mu_2$

Since we are testing if the means are different, we have a two-tailed test, which means that the p-value is the probability of the means differing by the amount they different on the sample, or a greater amount.

Hence, the interpretation is that there is a 0.006 = 0.6% probability of the sample means differing by the amount that they differed on the sample.

More can be learned about p-values at brainly.com/question/16313918

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