Discuss the strengths and weaknesses of each of the forecasting models Naïve approach, Simple moving average, Weighted moving average, Exponential smoothing and Linear regression

Given the table below, complete the missing cell values applying the Exponential Smoothing method of forecasting and Mean Absolute Deviation. Answer also the other 2 related questions below the table. Numbers with decimal should take 2 decimal places. Actual Quarter Tonnage Unloaded 1 2 3 4 5 6 7 8 175 160 170 160 160 170 180 200 Forecast for a=3 175 175.0 170.5 167.2 165.1 166.6 170.6 Sum of absolute deviation = Absolute Deviation for a = .3 Other questions: (1) What is the MAD for a = .3? (2) Which smoothing constant would you prefer? 0.00 15.00 0.50 10.35 4.93 13.45 29.41 80.89 Forecast for a = .6 175 166.0 168.4 163.4 161.3 166.5 174.6 Absolute Deviation for a = .6 0.00 15.00 4.00 8.40 3.36 8.66 13.46 25.38

How would you choose the appropriate number of factors to use in a forecasting model and how would you build a factor augmented VAR.

Describe the various types of time-series and associative forecasting models. Which types of organizations are each of these most applicable to, and why?

If month one has 240,000 demands, month two 250,080 demands, month three 325,00 demands, month four 370,000 demands, month five 420,000 demands and month six 509,00 demands. Use a forecast for the first month of 240,000, an initial trend forecast of 50,000, and smoothing parameters of 0.35 for both demand smoothing and trend smoothing. Compute the forecasts and trends using double exponential smoothing

Which of the following are common metrics for measuring the relative quality of different forecasting methods? OAbsolutely Mean Mean Squared Accuracy O Mean Absolute Percent Error Mean Squared Response OMean Squared Error Mean Absolute Error (a.k.a. Mean Absolute Deviation)

Forecasting can be classified into which basic types?

b. Compute 2s control limits for each forecast. (Do not round your intermediate calculations. Round your answers to 2 decimal places.) Forecast Method 1 Method 2 Control Limits