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: Week 1 2 3 4 Forecast Method 1 The MAD for Method 1 = 0.95 1.05 0.95 1.20 Actual Demand 0.72 1.00 1.00 1.00 Week 1 2 3 4 The mean squared error (MSE) for Method 2 = Forecast Method 2 0.82 1.20 0.88 1.17 Actual Demand thousand gallons (round your response to three decimal places). The mean squared error (MSE) for Method 1 = thousand gallons² (round your response to three decimal places). The MAD for Method 2 = thousand gallons (round your response to three decimal places). 0.72 1.00 1.00 1.00 thousand gallons (round your response to three decimal places).
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: Week 1 2 3 4 Forecast Method 1 The MAD for Method 1 = 0.95 1.05 0.95 1.20 Actual Demand 0.72 1.00 1.00 1.00 Week 1 2 3 4 The mean squared error (MSE) for Method 2 = Forecast Method 2 0.82 1.20 0.88 1.17 Actual Demand thousand gallons (round your response to three decimal places). The mean squared error (MSE) for Method 1 = thousand gallons² (round your response to three decimal places). The MAD for Method 2 = thousand gallons (round your response to three decimal places). 0.72 1.00 1.00 1.00 thousand gallons (round your response to three decimal places).
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter13: Regression And Forecasting Models
Section: Chapter Questions
Problem 34P: A small computer chip manufacturer wants to forecast monthly ozperating costs as a function of the...
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