04: HiTek Computer Services repairs and services personal computers at its store, and it makes local service calls. It primarily uses part-time university students as technicians. The company has had steady growth since it started. Managers purchase generic computer parts in volume at a discount from a variety of sources whenever they see a good deal. Thus, they need a good forecast of demand for repairs so that they will know how many computer component parts to purchase and stock, and how many technicians to hire. The company has accumulated the demand data shown in the accompanying table for repair and service calls for the past 12 months. Demand for Repair and Service Calls Period Month Demand 1 January 37 2 February 40 3 March 41 4 April 37 5 May 45 6 June 50 7 July 43 8 August 47 9 September 56 10 October 52 11 November 55 12 December 54 Compute a three-month weighted moving average forecasts with weights of 50%, 33% and 17%, reflecting the company's desire to have the most recent data influence the forecast most strongly. Compute exponential smoothing forecasts using a smoothing constant of 0.30. Use the Nalve approach to obtain the seed for the month of February Using MSE, explain by showing all calculations which of the above two methods provides more accurate forecasts. Compute the bias and tracking signals for both methods and explain why or why not they are in control