P1 = proportion of women catching cold
P2 = proportion of men catching cold
Null hypothesis: P1"\\geq" P2
Alternative hypothesis: P1 < P2
We can conclude that the drug is more effective for women than for men if null hypothesis is rejected
Using sample data, the pooled sample proportion (p) and the standard error (SE) is calculated:
p = [(0.38 * 100) + (0.51 * 200)] / (100 + 200) = 0.467
SE = { p * ( 1 - p ) * [ (1/n1) + (1/n2) ] }0.5 = [ 0.467 * 0.533 * ( 1/100 + 1/200 ) ]0.5 = 0.061
z-score:
z = (p1 - p2) / SE = (0.38 - 0.51)/0.061 = -2.13
P-value:
P(z < -2.13) = 0.017
Since the P-value (0.017) is greater than the significance level (0.01), we cannot reject the null hypothesis. We can't conclude that the drug is more effective for women than for men.
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