Suppose a market analyst wants to determine whether theaverage price of a gallon of whole milk in Seattle is greater thanAtlanta. To do so, he takes a telephone survey of21 randomly selected consumers in Seattle who havepurchased a gallon of milk and asks how much they paid for it. Theanalyst undertakes a similar survey in Atlanta with18 respondents. Assume thepopulation variance for Seattleis 0.03, the population variancefor Atlanta is 0.015, and that the price of milkis normally distributed. Given average price for Seattle is$2.52, and average price for Atlanta is$2.38.

(1). Use the correct R command to compute a 99%confidence level confidence interval of the difference in the meanprice of a gallon of milk between Seattle and Atlanta. (note: inthe R function, you need the value of standard deviation for bothsamples. You need to calculate the standard deviation based on thevariance, then plug the standard deviation values in the Rfunction) What are the lower bound and upper bound of theinterval?

(2). Using a 1% level of significance (alpha =0.01), manually test whether the average price of a gallonof whole milk in Seattle is greater than Atlanta. What isthe statistical decision and business decision?

(3). Using a 1% level of significance. Importdata set MilkPrice_S.csv and MilkPrice_A.csv files to R studio.Write the correct R commands for testing whether theaverage price of a gallon of whole milk in Seattle is greater thanAtlanta. What is the p value? What is the statisticaldecision and business decision?

Seattle
2.55
2.36
2.43
2.67
2.54
2.43
2.5
2.54
2.38
2.61
2.8
2.49
2.43
2.61
2.57
2.36
2.56
2.71
2.5
2.64
2.27 Atlanta 2.25 2.4 2.39 2.3 2.33 2.4 2.49 2.29 2.23 2.41 2.48 2.29 2.39 2.59 2.53 2.26 2.38 2.45