We must take care that we are accurately interpreting the results of our confide

Question

We must take care that we are accurately interpreting the results of our confidence intervals and hypothesis tests. Consider the scenario described below: We are testing the hypothesis "The mean weight of American men is greater than 180 lbs." The null hypothesis is H_0: mu = 180 and the alternative hypothesis is H_A: mu > 180. Further, we decide to test this hypothesis at significance level alpha = 0.05. Suppose we took a SRS of 100 American men and found that the average weight of our sample was greater than 180 and the p-value of the test was p = 0.02. Comment on the student responses below. Whose understanding of hypothesis testing is good? Whose is bad? Help straighten these students out with your insightful remarks.

Explanation / Answer

p-value =0.02 is less than level of significance =0.05. so, reject the null hypothesis.

we have eni=ough evidence against the null hypothesis.

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