A restaurant wants to test a new in-store 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. 18 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 (2.16, 23.32). Which of the following is the appropriate conclusion? The differences were calculated as (after ad campaign- before ad campaign).1) 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.2) There is not a significant difference between the average sales quantity before or after the ad campaign.3) We are 95% confident that the average difference in sales quantity for all stores is positive, with the higher sales being before the ad campaign.4) We are 95% confident that the average difference in sales quantity for all stores is negative, with the higher sales coming after the ad campaign.5) We are 95% confident that the average difference in sales quantity for all stores is positive, with the higher sales coming after the ad campaign.

The fifth option is the most correct option. We are 95% confident that the average difference in sales quantity for all stores is positive, with the higher sales coming after the ad campaign.

Step-by-step explanation: since they is 95% confidence interval to estimate the true average difference in nationwide sales quantity before the ad campaign and after is (2.16, 23.32). That's mean they will be a positive result for the difference.

The average difference before the ad campaign is 2.16, while the average difference after the ad campaign so 23.32.

Therefore the difference between after and before the ad campaign will be

23.32 - 2.16 = 21.16

It gave a positive result, because more sales came after the ad campaign.

The appropriate conclusion is Option 5.

5) We are 95% confident that the average difference in sales quantity for all stores is positive, with the higher sales coming after the ad campaign.

Step-by-step explanation:

Analysing the result of Confidence Interval of 95% with the statement in quote,

"The 95% confidence interval to estimate the true average difference in nationwide sales quantity before the ad campaign and after is (2.16, 23.32)", It can be seec that difference the values of the interval(23.32 - 2.16) is positive and the higher part is after the ad compaign (That is, 23.23)

(w – 2.5)(w + 2.5)

(–4v – 9)(–4v + 9)

step-by-step explanation: