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Problem 1 A grocery store designed to handle a maximum of one thousand customers per day has noticed an increase in popularity. It believes that the store will soon reach its maximum capacity but it wants to be certain. The store decided to look at its daily attendance for the past 300 days, and to develop a forecasting model to predict when it would reach capacity. Develop a forecast model using the data in file BA3653A3Q1.xlsx, found in D2L. Do not use the naive method. Should one model be used to model the entire data set? Consider if all the data should be used in creating your prediction. Answer the following questions: a. Using your model, predict how many days in the future it will take for the store to reach maximum capacity. b. Suppose an expansion can be made to increase capacity to 1500 customers/day. If the popularity increase continues, estimate how much more time (in days) it will take for the store to reach its new capacity after expansion. c. A manager is convinced that the naive method is the best at predicting customer usage. Show (using numbers) that your method is superior at creating forecasts. d. Another manager is concerned that there is too much random variation in the number of customers to be able to discern any pattern. Quantify the strength of the relationship to determine if there is too much random variation