2.26 A managed care organization would like to develop a prediction for enrollment in one of its Medicaid health plans. Enrollment data over the past forty-eight months is displayed in Table EX 2.26. Table EX 2.26 Year Month Enrollment 1 July 806 1 August 814 1 September 826 1 October 820 1 November 1,013 1 December 904 2 January 900 2 February 1,111 2 March 1,119 2 April 902 2 May 908 2 June 904 2 July 962 2 August 963 2 September 974 2 October 976 2 November 1,172 2 December 1,179 3 January 1,168 3 February 1,159 3 March 1,165 3 April 1,175 3 May 929 3 June 940 3 July 947 3 August 953 3 September 1,016 3 October 1,017 3 November 1,035 3 December 1,273 4 January 1,015 4 February 1,013 4 March 1,015 4 April 973 4 May 973 4 June 961 4 July 968 4 August 1,227 4 September 1,232 4 October 1,234 4 November 1,388 4 December 1,390 5 January 1,112 5 February 1,130 LO 5 March 1,136 5 April 1,125 5 May 1,130 5 June 1,084 5 July 1,086 5 August 1,374 5 September 1,369 5 October 1,373 a. Predict enrollment in November of year 5 using a five-period moving average. b. Predict enrollment in November of year 5 using the simple exponential smoothing model with a = 0.3. c. Predict enrollment in November of year 5 using linear regression. e. Calculate MAD and MAPE for the predictions developed in (a) through (c). f. Which prediction method would you recommend? Explain.