Answer:
There is no significant difference between the two proportions
Step-by-step explanation:
State the hypotheses:
Null hypothesis -> H0: P1 = P2
Alternative hypothesis -> H1: P1 not = P2
Note that hypotheses constitute a two-tailed test. the null hypothesis will be rejected if the proportion from population 1 is too big or if it is too small.
Formulate an analysis plan
For the analysis, the significance level is 0.05. The test method is a two-proportion z-test.
Analyze sample data.
Using sample data we calculate the pooled sample porportion (p) and the standard error (SE). Using those measures, we compute the z-score test statistic (z).
p = (p1*n1 + p2*n2)/(n1 + n2)
p1 = 45/80 = 0.5625
p2 = 63/120 = 0.525
n1 = 80
n2 = 120
p = (0.5625*80 + 0.525*120)/(80 + 120)
p = 0.54
SE = 0.07112
z = (p1 - p2)/ SE
z = (0.5625 - 0.525)/0.07112
z = 0.527
For z = 0.527 we have p-value 0.198
Interpret results. Since p - Value (0.198) of the test is greater than the alpha-0.05 (For two tailed test α-0.025). Therefore we cannot reject the null hypothesis.
There is no significant difference between the two proportions