3) Demand for sunflower oil in a small market is summarized as (in liters): Peri

Question

3) Demand for sunflower oil in a small market is summarized as (in liters): Period Demand 1 23 45 678 29.1 28.8 32.2 33.0 33.9 35.6 37.4 39.3 a) (5pts) Using the method of Moving Averages (for N-4) compute the single-period-ahead forecasts for periods 5, 6, 7, and 8. periods 5 through 8. Set the initial forecast Fs by taking the average of the first 4 periods. deviation (MAD). b) (5pts) Determine single period-ahe ad exponential smoothing forecasts with a 0.3 for c) (5pts) Compare the two approaches in part-(a) and part-(b) in terms of mean absolute 4) Considering the linear regression method for the data in Q.3: a) (10pts) Determine the forecasts for periods 5, 6, 7, and 8. b) (10pts) Do you think that linear regression is a better or worse approach than moving averages or exponential smoothing. How can you verify your answer. op

Explanation / Answer

Question 3(a)

Here for any month 4 month average will be calculated by taking average of previous 4 month average.

Here 4 months moving avergae with error

HEre 4 MA = average of previous 4 months and

Absolute Deviation = l yt - Ft l

Mean ABsolute Deviation MAD

Here Mean absolute division (MAD) = 1/4 * (3.125 + 3.625 + 3.725 + 4.325) =  3.7
(b) Exponential smoothing with alpha = 0.3

yt  = 0.3 yt-1 + 0.7Ft-1

Here Mean absolute division (MAD) = 1/4 * (3.125 + 3.888 + 4.521 + 5.065) = 4.1497

(c) Here 4 Month average method is better as it has low MAD.

Question 4

Here linear regression equationn is y^ = 1.494x + 26.93

This trendline is calculated with the help of linear regression model.

MAD with trend line = 1/4 * (0.5 + 0.294 + 0.012 + 0.418) = 0.306

so linear trend equation is better than any other method as it has lower MAD

Period Demand 4MA Forecast Absolute Error 1 29.1 2 28.8 3 32.2 4 33 5 33.9 30.775 3.125 6 35.6 31.975 3.625 7 37.4 33.675 3.725 8 39.3 34.975 4.325

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