Following are two weekly forecasts made by two different methods for the number of galions of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels in thousands of gallons Week 1 2 3 4 Forecast Method 1 0.85 108 0.92 122 Actual Demand 0.70 105 1:07 1.00 Week 1 2 3 4 Forecast Method 2 0.77 1.21 0.88 111 Actual Demand 0.70 1 05 107 1 00 The MAD for Method 1 -thousand gallons (round your response to three decimal places) The MAD for Muthod 2-thousand gallons cround your response to three decimal cos) As you can see in the following table demand for heart transplant surgery at Washington General Hospital has increased steadily in the past few years Year 1 2 3 5 Heart Transplants 46.0 520 530 570 58.0 The director of medical services predicted 6 years ago that demand in year 1 would be 420 surgeries a) Using exponential smoothing with ot 60 and the given forecast for your 1, the forecast for yoars 2 through 6 ore (rowd your responses to one docimal place) Year 1 2 3 + 56 Forecast 420 444 49 51458567 For the forecast made using exponechal moothing with a 000 and the given txecast for you 1 MAD Oures (rouw/ your responses to oro commor place) Sales of quilt covers at Bud Banis's discount department store in Carbondale over the past year are shown below Management prepared a forecast using a combination of exponential smoothing and its collective judgment for the 4 months (March April May and June) 0 Month Unit Sales Management's Forecast Jul 98 Aug 93 Sep 95 Oct 110 Nov 120 Dec 118 Jan 92 Feb 85 Mar 101 122 Apr 98 115 May 89 112 Jun 112 108 a) MAD for the forecast developed by the managements technique = [] sales (round your response to wo decimal places)