Using the data shown in the accompanying contingency table, test whether the population proportions differ at the = 0.05 level of significance by determining (a) the null and alternative hypotheses, (b) the test statistic, and (c) the P-value. Assume that the samples are dependent and were obtained randomly. Click the icon to view the contingency table. (a) Let p, represent the proportion of success for treatment A and p, represent the proportion of success for treatment B. What are the null and alternative hypotheses? OA. Ho: P1 = P2 H1: P1 #P2 O B. Ho: P1 =P2 H1: P1 > P2 O C. Ho: P1 =P2 H1: P1
Using the data shown in the accompanying contingency table, test whether the population proportions differ at the = 0.05 level of significance by determining (a) the null and alternative hypotheses, (b) the test statistic, and (c) the P-value. Assume that the samples are dependent and were obtained randomly. Click the icon to view the contingency table. (a) Let p, represent the proportion of success for treatment A and p, represent the proportion of success for treatment B. What are the null and alternative hypotheses? OA. Ho: P1 = P2 H1: P1 #P2 O B. Ho: P1 =P2 H1: P1 > P2 O C. Ho: P1 =P2 H1: P1
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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
Transcribed Image Text:Using the data shown in the accompanying contingency table, test whether the population proportions differ at the a = 0.05 level of significance by determining (a) the
null and alternative hypotheses, (b) the test statistic, and (c) the P-value. Assume that the samples are dependent and were obtained randomly.
Click the icon to view the contingency table.
(a) Let p, represent the proportion of success for treatment A and p, represent the proportion of success for treatment B. What are the null and alternative
hypotheses?
A. Ho: P1 = P2
H1: P1 # P2
B. Ho: P1 = P2
H1: P1 > P2
Ho: P1 = P2
H1: P1 <P2
D. Ho: P1 # P2
H1: P1 = P2
(b) The test statistic x6 is
(Round to two decimal places as needed.)
Contingency Table
Treatment A
Success
Failure
Success
43
26
Treatment B
Failure
28
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