Question 5: You work for the consumer insights department of a major big box retailer and you are investigating the efficacy of a new email marketing campaign. Through the use of email analytics research, you have determined that in a sample of 981 monitored subscribers, 289 of them opened the email within 24 hours of receiving it. What is the 95% confidence interval for the true proportion of all email subscribers that opened the email within 24 hours of receiving it?









Question 6: Based on past data, the producers of
Ice Mountain bottled water knew that the proportion of people who
preferred Ice Mountain to tap water was 0.691. To see how consumer
perception of their product has changed, they decide to conduct a
survey. Of the 84 respondents, 63 indicated that they preferred Ice
Mountain to the tap water in their homes. The 90% confidence
interval for this proportion is ( 0.6723 , 0.8277 ). What is the
best conclusion of those listed below?









Question 7: A restaurant wants to test a new
instore marketing scheme in a small number of stores before
rolling it out nationwide. The new ad promotes a premium drink that
they want to increase the sales of. 15 locations are chosen at
random and the number of drinks sold are recorded for 2 months
before the new ad campaign and 2 months after. The 95% confidence
interval to estimate the true average difference in nationwide
sales quantity before the ad campaign and after is (36.7, 12.86).
Which of the following is the appropriate conclusion? The
differences were calculated as (after ad campaign before ad
campaign).









5. Given that x= 289 and sample size n = 981
Confidence level is 95 % hence Z crtical at 95 % confidence level is 1.96
as Confidence interval as
Where E= Margin of error calculated as
p=x/n = 0.2946
Hence E calculated as
0.015, Hence Confidence interval
5) (0.26607 to 0.32312)
Question no 6.
According to question the conclusion will be
1) The proportion of Consumer who prefer ice mountain is 0.691 Wuth 90 % confidence.
Question no 7.
According to ths question the conclusion will be
4). We are 95% confident that the average difference in sales quantity for all stores is negative, with the higher sales being before the ad campaign.
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