HiTek Computer Services repairs and services personal computers at its store, and it makes local service calls. It primarily uses part-time State University students as technicians. The company has had steady growth since it started. It purchases 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 data shown in the accompanying table for repair and service calls for the past 12 months. 3.1. In the following table, please calculate the forecast using smoothing constants (α) equal to 0.30 Forecast, F(t+1) Period Month Demand α = 0.30 α = 0.50 1 January 37 2 February 40 37.00 3 March 41 38.50 4 April 37 39.75 5 May 45 38.37 6 June 50 41.68 7 July 43 45.84 8 August 47 44.42 9 September 56 45.71 10 October 52 50.85 11 November 55 51.42 12 December 54 53.21 13 January --- 53.61 3.2 The company has also calculated the exponential smoothing forecasts using smoothing constants (α) equal to 0.50 (provided above). What can you say about the responsiveness of the two forecasts? Which one is likely to be more responsive? 3.3. The company wants to compare the accuracy of these two different forecasts using MAD. Please compute MAD for (α) equal to 0.30 and (α) equal to 0.50 compared to the actual demand data. Which alpha provides a more accurate forecast? Describe why it might be more accurate.