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Following are two weekly forecasts made by two different methods for the number

ID: 410364 • Letter: F

Question

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 Forecast Week Method 1 Actual Demand 0.70 0.98 1.07 1.00 Forecast Method 2 0.82 1.21 0.90 1.15 Actual Demand 0.70 0.98 1.07 1.00 Week 0.90 1.08 0.97 1.17 4 The MAD for Method 1 thousand gallons (round your response to three decimal places) The mean squared error (MSE) for Method 1thousand gallons (round your response to three decimal places) The MAD for Method 2 thousand gallons (round your response to three decimal places) The mean squared error (MSE) for Method 2thousand gallons (round your response to three decimal places)

Explanation / Answer

Following table calculates and presents values of absolute deviations and Squared error under both Forecast method

Following are to be noted :

Absolute deviation = Absolute difference in values of Actual demand and corresponding forecast value

Squared error = Absolute deviation^2

MAD = Sum of values of Absolute deviation / 4 ( i.e. number of observations)

Mean Squared error ( MSE ) = Sum of values of Squared error / 4

Week

Actual demand

Forecast method 1

Absolute Deviation

Squared error

Forecast method 2

Absolute Deviation

Squared error

1

0.7

0.9

0.2

0.04

0.82

0.12

0.0144

2

0.98

1.08

0.1

0.01

1.21

0.23

0.0529

3

1.07

0.97

0.1

0.01

0.9

0.17

0.0289

4

1

1.17

0.17

0.0289

1.15

0.15

0.0225

SUM:

0.57

0.0889

0.67

0.1187

Therefore,

MAD for Method 1 = 0.57 / 4 = 0.142 Thousand Gallons

Mean Squared error ( MSE) for Method 1 = 0.0889 / 4 = 0.022 Thousand Gallon Square

MAD for method 2 = 0.67/4 = 0.167 Thousand Gallons

Mean squared error ( MSE ) for Method 2 = 0.1187 / 4 = 0.29 thousand Gallon Square

Week

Actual demand

Forecast method 1

Absolute Deviation

Squared error

Forecast method 2

Absolute Deviation

Squared error

1

0.7

0.9

0.2

0.04

0.82

0.12

0.0144

2

0.98

1.08

0.1

0.01

1.21

0.23

0.0529

3

1.07

0.97

0.1

0.01

0.9

0.17

0.0289

4

1

1.17

0.17

0.0289

1.15

0.15

0.0225

SUM:

0.57

0.0889

0.67

0.1187