Answer:
Step-by-step explanation:
a) We would set up the hypothesis test.
For the null hypothesis,
H0 : p ≥ 0.25
For the alternative hypothesis,
H1 : p < 0.25
b) from the given information,the sample proportion or point estimate for the population proportion is
1219/3532 = 0.35
Confidence interval = sample proportion ± margin of error
Margin of error = z × √pq/n
p = 0.35
q = 1 - 0.35 = 0.65
z score for 95% confidence level is 1.96
Margin of error = 1.96 × √(0.35 × 0.65)/3532 = 0.016
Confidence interval = 0.35 ± 0.016
c) Given that the 95% confidence interval is (0.329 , 0.361), it means that the lower limit of the confidence interval is 0.329 and the upper limit is 0.361
If more than a quarter of all North Americans have hypertension. It means that the true proportion can be within this interval. 95% confidence interval is a high degree of confidence. Therefore, we can say that with a high degree of confidence that more than a quarter of all North Americans have hypertension.
d) it would get narrower