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1) Removing the seasonal component from a historical demand (de-seasonalizing)

Question : 1) Removing the seasonal component from a historical demand (de-seasonalizing) : 2065990

1) Removing the seasonal component from a historical demand (de-seasonalizing) can be accomplished by dividing each data point by its appropriate seasonal index.

2) If a pattern appears like cycles or seasonality when a dependent variable is plotted against time, one should use time series analysis instead of regression analysis.

3) Seasonal indices can be used to de-seasonalize demand or incorporate seasonality into a forecast.

4) Simple linear regression is used as a forecasting technique when there are multiple independent variables.

5) The Fresh Express Beverage Company is interested in evaluating the effects of advertising spend on the sales of their products. Based on historical data, they develop the following equation which approximates this relationship: y = 2.5 + 0.02x, where y is the number of bottles of beverages sold measured in millions of units, and x = amount of money spent on advertising measured in millions of dollars. Based on this information, which of the following statements is correct?

A) Every additional million dollars spent on advertising will increase the beverage sales by 200,000 units.

B) The Company will sell a minimum of 2.5 million units even if no money is spent on advertising.

C) Every additional 20,000 dollars spent on advertising will increase the beverage sales by a million units.

D) The number of units of beverage sold will decrease beyond a certain amount of money spent on advertising.

 

 

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