Final answer:
To answer the student's question, the 95% confidence interval for the difference in proportions is calculated using the formula for two proportions. Additionally, a hypothesis test is performed to determine if death rates from cardiovascular disease are higher among men with high blood pressure, involving setting hypotheses, calculating a test statistic, and making a conclusion based on the results.
Step-by-step explanation:
Calculating 95% Confidence Interval for the Difference in Proportions
To calculate the 95% confidence interval for the difference between the observed proportions of deaths from cardiovascular disease in the low and high blood pressure groups, we will use the following formula:
(p1 - p2) ± z* sqrt(p1*(1-p1)/n1 + p2*(1-p2)/n2)
Where p1 and p2 are the observed proportions in the low and high blood pressure groups, n1 and n2 are the total number of individuals in the groups, and z* is the z-value corresponding to the 95% confidence level (approximately 1.96).
First, we calculate the proportions:
p1 = 21/2676 and p2 = 55/3338.
Next, we input these into the formula with the respective group sizes to find the confidence interval.
Hypothesis Testing for Difference in Proportions
To test the hypothesis that death rates from cardiovascular disease are higher among men with high blood pressure, we perform a test of significance for the difference in proportions. The null hypothesis (H0) states there is no difference in death rates, while the alternative hypothesis (H1) suggests that the death rate is higher for the high blood pressure group. The steps involve calculating the test statistic and comparing it to a critical value or using a p-value approach. A conclusion is drawn based on this comparison.
For this case, details of the test calculation are not provided, but a general process has been outlined.