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.
At the null hypothesis, it is tested if the means are equal, that is:
[tex]H_0: \mu_1 = \mu_2[/tex]
At the alternative hypothesis, it is tested if the means are different, that is:
[tex]H_1: \mu_1 \neq \mu_2[/tex]
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 https://brainly.com/question/16313918
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