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. 20 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 90% confidence interval to estimate the true average difference in nationwide sales quantity before the ad campaign and after is (3.96, 28.79). Which of the following is the appropriate conclusion? 1) We are certain the average difference in sales quantity between after the ad campaign to before for all stores is between -3.83 and 1.83.
2) We are 95% confident that the difference between the average sales after the ad campaign and the average sales before the ad campaign is between-3.83 and 1.83.
3) The proportion of all stores that had a difference in sales between after the ad campaign to before is 95%.
4) We are 95% confident that the average difference in the sales quantity after to before of the stores sampled is between -3.83 and 1.83.
If a random sample of 20 persons weighed 3,460, the sample mean x-bar would be 3460/20 = 173 pounds. The z-score for 173 pounds is given by: Referring to a standard normal distribution table, and using z = 0.66, we find: Therefore The answer is: 0.2546
