Answer:
Explanation:
We would set up the hypothesis test.
For the null hypothesis,
p = 0.32
For the alternative hypothesis,
p ≠ 0.32
This is a two tailed test
Considering the population proportion, probability of success, p = 0.32
q = probability of failure = 1 - p
q = 1 - 0.32 = 0.68
Considering the sample,
Sample proportion, P = x/n
Where
x = number of success = 261
n = number of samples = 750
P = 261/750 = 0.35
We would determine the test statistic which is the z score
z = (P - p)/√pq/n
z = (0.35 - 0.32)/√(0.32 × 0.68)/750 = 1.8
Recall, population proportion, p = 0.32
The difference between sample proportion and population proportion(P - p) is 0.35 - 0.32 = 0.03
Since the curve is symmetrical and it is a two tailed test, the p for the left tail is 0.32 - 0.03 = 0.29
the p for the right tail is 0.32 + 0.03 = 0.35
These proportions are lower and higher than the null proportion. Thus, they are evidence in favour of the alternative hypothesis. We will look at the area in both tails. Since it is showing in one tail only, we would double the area
From the normal distribution table, the area above the z score in the right tail 1 - 0.9641 = 0.0359
We would double this area to include the area in the right tail of z = 0.44 Thus
p = 0.0359 × 2 = 0.07
Since alpha, 0.05 < the p value, 0.07 then we would fail to reject the null hypothesis. Therefore, this is not sufficient evidence to conclude that the actual percentage is different from 32% at the 5% significance level.