Question 29. The 1 obeerved sales for January, February, March and April are 113

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Question 29. The 1 obeerved sales for January, February, March and April are 113, 122, 130 and 16, respectively. What are the given forecast? respectively. Suppose the forecasted sales for these months were 105, 127, 133 and 115, A. MAE =-0.25 and MSE = 4.25 B. MAE = 0.25 and MSE = 24.75 MSE= 4.25 D. MAE= 4.25 and MSE-2475 C. MAE = 0.25 and Question 30. An unbiased forecast is: A·consistently equal to actual demand B. consistently above actual demand C. consistently below actual values D. sometimes above and sometimes below the actual demand Question 31. A company should use subjective forecasting method, when A. it does not have historical data, B. it does not have enough time, C. it does not skilled forecaster, D. it does not require high forecast accuracy. Questions 32 to 36 are on the process described by the following process flow diagram: Each box describes an activity along with time required to carry out the activity. The arrows show direction of the How based activities: Two arrows coming out from an activity imply that the activity generates inputs for two different activitics (which can be done in paralled). Two arrows coming into an activity imply that the activity roquires output from two different activitics (which can be done in parallel) 6 hours 8 hours 3 hours 5 hours C 10 hours - 4 hours Question 32. What is the minimum flow time for a job in this process? A. 20 hours B. 22 hours C. 24 hours D. 36 hours Question 33. Which of the following reduces the theoretical low time (TFT) for a job by 4 hours? A. reducing time for C and D by 2 hours each C. reducing time for B and D by 2 hours each B. reducing time for B and C by 2 hours each D. reducing time for E and F by 2 hours each

Explanation / Answer

29. D. MAE = 4.25, MSE = 24.75

MAE is calculated as the mean of absolute errors. Absolute error is the absolute difference between observed sales and forecast:

MAE = (|113-105|+|122-127|+|130-133|+|116-115|)/4 = 4.25

MSE is calculated as the mean of squared errors. Squared error is the square of difference between observed sales and forecast:

MAE = ((113-105)2+(122-127)2+(130-133)2+(116-115)2)/4 = 4.25

Month Sales Forecast Absolute Error Squared Error January 113 105 8 64 February 122 127 5 25 March 130 133 3 9 April 116 115 1 1 4.25 24.75 MAE MSE

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