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(a) A firm uses simple exponential smoothing with a = 0.1 to forecast demand. The forecast for the week of January 1 was 500
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Answer #1

(a)

Exponential moving forecast for the week of January 8 = (actual demand of Jan1 - EMA of Jan1)*α + EMA of Jan1

Exponential moving forecast for the week of January 8 = (450 – 500)*.1 + 500

Exponential moving forecast for the week of January 8 = 495

(b)

In causal model, cause and effect is established between dependent and independent variables. One or a set of independent variables makes impact upon the one dependent variable. It is established through the causal model of forecasting. In contrast to it, time series model takes time into the consideration and eliminate the impact of seasonality to smoothen the data. It helps in forecasting the future.

In causal model, value of dependent variable lies up the value of the independent variable. But, in time series model, past data of the variable is taken for analysis.

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