Answer:
Yes, there is enough evidence to say the proportions are the same.
Step-by-step explanation:
Null hypothesis: The proportions are the same.
Alternate hypothesis: The proportions are not the same.
Data given:
p1 = 51% = 0.51
n1 = 200
p2 = 48% = 0.48
n2 = 150
pooled proportion (p) = (n1p1 + n2p2) ÷ (n1 + n2) = (200×0.51 + 150×0.48) ÷ (200 + 150) = 174 ÷ 350 = 0.497
Test statistic (z) = (p1 - p2) ÷ sqrt[p(1-p)(1/n1 + 1/n2) = (0.51 - 0.48) ÷ sqrt[0.497(1-0.497)(1/200 + 1/150)] = 0.03 ÷ 0.054 = 0.556
The test is a two-tailed test. At 0.10 significance level the critical values -1.645 and 1.645
Conclusion:
Fail to reject the null hypothesis because the test statistic 0.556 falls within the region bounded by the critical values.
