Following are two weekly forecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of gallons: Actual Method 2 Demand Forecast Week 1 2 3 Forecast Method 1 0.95 1.08 0.97 1.20 Actual Demand 0.70 1.00 1.00 1.04 Week 1 2 3 4 0.70 1.00 0.80 1.21 0.90 1.11 1.04 The MAD for Method 1 - thousand gallons (round your response to three decimal places) The mean squared error (MSE) for Method 1 - thousand gallons (round your response to three decimal places) The MAD for Method 2 thousand galons (round your response to three decimal places) The mean squared error (MSE) for Method 2 thousand gallons fround your response to three decimal places) Lori Cook has developed the following forecasting model: y = 36.0 + 4.20x, where = demand for Kool Air conditioners and x = the outside temperature (degrees Fahrenheit) a) When the temperature outside is 70 F, demand forecast air conditioners (enter your response as an integer). b) When the temperature outside is 80 F, demand forecast - air conditioners (enter your response as an integer). c) When the temperature outside is 90 F, demand forecast - air conditioners (enter your response as an integer)