Examine these two graphs and based on the demand pattern and axis scaling, recommend a forecasting technique (and the required parameters) that would work best for each one. Justify your recommendations
What will be an ideal response?
Answer: Demand Pattern A shows a strong linear trend from 103 up to 207 but Demand Pattern B fluctuates around 169 and (with a standard deviation of 4) is purely random. Adjusted exponential smoothing or linear regression are the only suitable methods for Demand Pattern A. A linear equation of the form Y = 95.98 + 5.82X yields an R squared of 0.99. The randomness in Demand Pattern B is pure noise and therefore not predictable. Moving averages with a large n or exponential smoothing with a low alpha will smooth this randomness but don't truly add much in the way of predictive ability.
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A clothing store buys dresses and sells them for a higher price. It has no other variable costs, but it incurs fixed costs of salespeople and rent. If the number of dresses purchased and sold increases (assuming the purchase and sale prices do not change), the store's profit margin:
a) increases b) decreases c) stays the same
The "equalization phenomenon" refers to the equal effectiveness of co-located and distributed teams
a. True b. False