Answer:
we will fail to reject the null hypothesis and conclude that there's insufficient evidence to support the claim that the percentage is actually more than the reported percentage
Explanation:
We are given;
Population proportion; p = 30% = 0.3
Sample proportion; p^ = 37% = 0.37
Sample size; n = 100
Let's define the hypotheses;
Null hypothesis; H0: p ≤ 0.3
Alternative hypothesis; Ha: p > 0.3
Formula for the test statistic is;
z = (p^ - p)/√(p(1 - p)/n)
Thus;
z = (0.37 - 0.3)/√(0.3(1 - 0.3)/100)
z = 0.07/0.04582575695
z = 1.53
From z-distribution table, at z=1.53 we have;
p-value = 1 - 0.9370 = 0.063
This p-value is greater than the significance level of 0.02 and thus we will fail to reject the null hypothesis and conclude that there's insufficient evidence to support the claim that the percentage is actually more than the reported percentage