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5) Susan is estimating an engineering project future demand levels. The historical data on hand shows high variability and she doesn't know what alpha to use in the exponential smoothing method. What should you recommend to Susan? A) Using a low value of alpha in this situation seems OK. B) You recommend to use a high value of alpha. C) A moderate alpha should be better in this situation. D) Alpha should be zero. E) Alpha should be 1.3 or higher 6) In weighted average forecasting, which of the following is false? A) The summation of weights should be one B) The method should be measured using any metric of error before implementation C) The most recent data has the higher weight D) The oldest data should have higher weight E) The weights can be calibrated to provide better results 7) In simple moving averages, which of the following is true? A) Simple moving averages will always be the most accurate method for forecasting B) MA(4) will be more reactive to changes than MA(7) C) MA(2) will be more stable than MA(3) D) MA(5) will be less reactive to changes than MA(6) E) Simple moving averages rarely provide an accurate answer 8) When the historical data appears to be increasing values in a relatively stable manner, we say that: A) A simple moving average with big n will provide minimum error B) Simple exponential smoothing might be advisable C) Linear Regression will predict the data more accurately D) Seasonal Adjustment may be required E) A trend is present 9) Which of the following forecasting methods require the least calculation? A) MA(4) B) M(5) C) Nave D) Exponential Smoothing, alpha=0.3 E) Adjusted Exponential Smoothing, alpha=0.5, beta=0.3 10) Adjusted exponential smoothing produces a regular exponential smoothing when: A) The trend is equal to 1 B) There is no trend C) Beta = zero D) Alpha = zero E) The data is increasing steadily