Clinton Urgent Care service opened in early 2012 to provide health care service to patients who needed to see a physician urgently, but did not have a condition that called for an emergency. Since the number of patients that came every day varied, Martha Jones, the manager of Clinton, found it difficult to schedule staff. The service opened from 8 a.m. to 8 p.m. every day. Often staff had to stay longer due large number of patients waiting for service.
She approached Gary Adams, a recent graduate of UHD who had received an "A" in MGT 3332, to help her out to do a better job of forecasting. Gary shuffled over his old notes and thought he could use what he had learned in MGT 3332. He recalled that in such cases Time Series data could be useful. So, he asked Martha to provide him the recent patient data.
Martha went back to her office and compiled the past data as shown in Table below.
Date No. of Patients Date No. of Patients
8/1/2014 63 8/16/2014 80
8/2/2014 70 8/17/2014 79
8/3/2014 65 8/18/2014 88
8/4/2014 72 8/19/2014 88
8/5/2014 82 8/20/2014 85
8/6/2014 70 8/21/2014 90
8/7/2014 75 8/22/2014 72
8/8/2014 81 8/23/2014 95
8/9/2014 70 8/24/2014 88
8/10/2014 75 8/25/2014 98
8/11/2014 65 8/26/2014 95
8/12/2014 98 8/27/2014 99
8/13/2014 78 8/28/2014 89
8/14/2014 80 8/29/2014 95
8/15/2014 82 8/30/2014 98
8/31/2014 96

A. Plot a scatter diagram of the above data. Do you think time series models will be useful for forecasting in such a situation?
B. Determine a linear trend line for forecasting. Use your trend equation to forecast for the date of your birthday in month of September. (If your birthday is 5th November, forecast for 5th September. If your birthday is 25th February, forecast for 25th September).
C. Assume the forecast on 8/21/2014 was same as the actual, forecast for September 1, using exponential smoothing method. Use alpha=0.3 if your birthdate is an odd number; use alpha = 0.6, it is an even number. Use Excel for this exercise.