In clinical trials of a medication, 2055 subjects were divided into two groups. The 1536 subjects in group 1 received the medication. The 519 in group 2 received a placebo. Of the 1536 subjects in group 1, 57 experienced dizziness as a side effect. In group 2, 13 experienced dizziness as a side effect. To test whether the proportion experiencing dizziness in group 1 is greater than that in group 2, the researchers entered the data into statistical software and obtained the following results. Test at a = 0.01. Sample p Estimate for p(1) - p(2): 0.012061 0.037109 95% Cl for p(1) – p(2): (– 0.004374, 0.028496) 0.025048 Test for p(1) – p(2) = 0 (vs > 0): z = 1.31 P-value = 0.095 Sample 1536 519 57 2 13 (This is a reading assessment question. Be certain of your answer because you only get one attempt on this question.) What conclusion can be drawn at the a = 0.01 level of significance? O A. Do not reject Ho, there is not enough evidence to conclude that the proportion experiencing dizziness in group 1 is greater than the proportion experiencing dizziness in group 2. O B. Reject Ho, there is not enough evidence to conclude that the proportion experiencing dizziness in group 1 is greater than the proportion experiencing dizziness in group 2. O C. Reject Ho, there is enough evidence to conclude that the proportion experiencing dizziness in group 1 is greater than the proportion experiencing dizziness in group 2. O D. Do not reject Ho, there is enough evidence to conclude that the proportion experiencing dizziness in group 1 is greater than the proportion experiencing dizziness in group 2.

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2-Proportion Test

In a 2-proportion test, two separate proportions are measured at the same time, and their similarity is evaluated. It is also known as a 2-proportion z-test, and a comparison of two different proportions is done in this method.