Answer:
A confidence interval and hypothesis test will yield the same results when the null hypothesis value is outside the calculated confidence interval. In other words, if the null hypothesis falls outside the confidence interval, the null hypothesis is rejected at the same level of significance used to calculate the confidence interval. Conversely, if the null hypothesis falls inside the confidence interval, it cannot be rejected.
Null hypothesis: The proportion of college students who believe that freedom of the press is secure or very secure in this country has not changed from 2016.
Alternative hypothesis: The proportion of college students who believe that freedom of the press is secure or very secure in this country has changed from 2016.
We can test this hypothesis using a two-sample z-test for proportions, where the two proportions being compared are the proportion of students who believed freedom of the press was secure or very secure in 2016 and the proportion who believed this in 2017. The test statistic is calculated as:
z = (p1 - p2) / sqrt( p(1-p) * (1/n1 + 1/n2) )
where p1 is the proportion of students who believed freedom of the press was secure or very secure in 2016, p2 is the proportion who believed this in 2017, n1 is the sample size for 2016, n2 is the sample size for 2017, and p is the pooled proportion of successes.
If the test statistic falls outside the critical values for the chosen level of significance, the null hypothesis can be rejected and we can conclude that the proportion of college students who believe that freedom of the press is secure or very secure in this country has changed from 2016.
Explanation: