Tom and Kelly are studying confidence intervals and hypothesis tests for one parameter of a population. To understand the concepts and ideas, they are practicing some exercises form their textbook. In one of the examples, they should construct a two-sided hypothesis test on an unknown population proportion to check the validity of a claim that the population proportion is 60%. Kelly solves the problem by finding the acceptance region and concludes that at a 5% level of significance, the claim is not accepted. Tom suggests solving this problem with the p-value and seeing if the outcomes are identical. He finds the p-value of the problem equals to 2% and his result does match with Kelly's result. Kelly says there is also a third way to check the validity of the claim. Tom is surprised and asks what the third way is? Kelly says we can also form a 95% confidence interval to check the validity of the claim and the outcome must be consistent with our results. Tom says I thought there were only two ways to check the validity of a claim including acceptance region and p-value; I am wondering how this problem could be solved with a confidence interval? What would you think about Kelly's response to Tom's question?