Question

In marketing, response modeling is a method for identifying customers most likely to respond to an advertisement. Suppose that in past campaigns 31.6% of customers identified as likely respondents did not respond to a nationwide direct marketing campaign. After making improvements to their model, a team of marketing analysts hoped that the proportion of customers identified as likely respondents who did not respond to a new campaign would decrease. The analysts selected a random sample of 1500 customers and found that 441 did not respond to the marketing campaign. The marketing analysts want to use a one-sample z-test to see if the proportion of customers who did not respond to the advertising campaign, $p$, has decreased since they updated their model. They decide to use a significance level of $\alpha = 0.05$. Select the correct null ($H_0$) and alternative ($H_1$) hypotheses. $H_0: p = 0.294$ and $H_1: p < 0.294$ $H_0: p = 0.316$ and $H_1: p \neq 0.316$ $H_0: p = 0.316$ and $H_1: p < 0.316$ $H_0: p = 0.316$ and $H_1: p < 0.316$ $H_0: p = 0.294$ and $H_1: p < 0.294$ Determine the value of the z-statistic. Give your answer precise to at least two decimal places. -3.69 Incorrect Determine the $P$-value for this test. Give your answer precise to at least three decimal places. 0.0002 P-value: Incorrect

          In marketing, response modeling is a method for identifying customers most likely to respond to an advertisement. Suppose that in past campaigns 31.6% of customers identified as likely respondents did not respond to a nationwide direct marketing campaign. After making improvements to their model, a team of marketing analysts hoped that the proportion of customers identified as likely respondents who did not respond to a new campaign would decrease. The analysts selected a random sample of 1500 customers and found that 441 did not respond to the marketing campaign.
The marketing analysts want to use a one-sample z-test to see if the proportion of customers who did not respond to the advertising campaign, $p$, has decreased since they updated their model. They decide to use a significance level of $\alpha = 0.05$.
Select the correct null ($H_0$) and alternative ($H_1$) hypotheses.
$H_0: p = 0.294$ and $H_1: p < 0.294$
$H_0: p = 0.316$ and $H_1: p \neq 0.316$
$H_0: p = 0.316$ and $H_1: p < 0.316$
$H_0: p = 0.316$ and $H_1: p < 0.316$
$H_0: p = 0.294$ and $H_1: p < 0.294$
Determine the value of the z-statistic. Give your answer precise to at least two decimal places.
-3.69
Incorrect
Determine the $P$-value for this test. Give your answer precise to at least three decimal places.
0.0002
P-value:
Incorrect

In marketing, response modeling is a method for identifying customers most likely to respond to an advertisement. Suppose that in past campaigns 31.6% of customers identified as likely respondents did not respond to a nationwide direct marketing campaign. After making improvements to their model, a team of marketing analysts hoped that the proportion of customers identified as likely respondents who did not respond to a new campaign would decrease. The analysts selected a random sample of 1500 customers and found that 441 did not respond to the marketing campaign.
The marketing analysts want to use a one-sample z-test to see if the proportion of customers who did not respond to the advertising campaign, p, has decreased since they updated their model. They decide to use a significance level of α = 0.05.
Select the correct null (H0) and alternative (H1) hypotheses.
H0: p = 0.294 and H1: p < 0.294
H0: p = 0.316 and H1: p ≠ 0.316
H0: p = 0.316 and H1: p < 0.316
H0: p = 0.316 and H1: p < 0.316
H0: p = 0.294 and H1: p < 0.294
Determine the value of the z-statistic. Give your answer precise to at least two decimal places.
-3.69
Incorrect
Determine the P-value for this test. Give your answer precise to at least three decimal places.
0.0002
P-value:
Incorrect

Added by Amanda M.

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