Week Four Homework Assignment Ajax Manufacturing is an electronic test equipment manufacturing firm that markets a certain piece of specialty test equipment. Ajax has several competitors who currently market similar pieces of equipment. While customers have repeatedly indicated they prefer Ajax's test equipment, they have historically proven to be unwilling to wait for Ajax to manufacture this certain piece of equipment on demand and will purchase their test equipment from Ajax's competitors in the event Ajax does not have the equipment available in inventory for immediate delivery. Thus, the key to Ajax successfully maintaining market share for this particular piece of equipment has been to have it available in stock for immediate delivery. Unfortunately, it is a rather expensive piece of equipment to maintain in inventory. Thus, the president of Ajax Manufacturing is very interested in accurately forecasting market demand in order to ensure he has adequate inventory available to meet customer demand without incurring undue inventory costs. His sales department has provided the following historical data regarding market demand for this certain piece of specialty electronics test equipment for the past 24 months. Time Period 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Actual Number of Units Sold 33 36 32 35 33 36 34 38 37 36 38 38 37 39 35 38 37 39 37 35 37 34 35 1 24 36 Hint: For questions 23 through 25, you need to keep in mind that the projected demand for the test equipment for time period 25 derived by the forecasting model is only a point estimate (this concept was discussed in week one relative to the mean). While a point estimate is a precise value, it is not necessarily an accurate value since the various measures of forecasting accuracy (i.e., MAD, MSE and MAPE) tell us there is some potential degree of error associated with using the forecasting model to predict salary values. In order to answer questions 23 through 25 you will need to create an interval estimate (this concept was also discussed during week one relative to the mean) for the projected demand for the test equipment for time period 25. To calculate the interval estimate projected demand for the test equipment for time period 25, simply subtract the measure of forecasting error value from the projected demand for the test equipment for time period 25 to define the lower limit of the interval estimate and add this value to the projected demand for the test equipment for time period 25 to define the upper limit for the interval estimate. 1. What is the projected demand for the test equipment for time period 25 based upon using a 3-month moving average forecast model? a. What are the bias, mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE) for the 3-month moving average forecast for time periods 4 through 24? 2. What is the projected demand for the test equipment for time period 25 based upon using a 3-month weighted moving average forecast model for which the weighting factor for actual demand one month ago is 3, the weighting factor for actual demand two months ago is 2, and the weighting factor for actual demand three months ago is 1? a. What are the bias, mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE) for the 3-month weighted moving average forecast for time periods 4 through 24? 3. What is the projected demand for the test equipment for time period 25 based upon using an exponential smoothing forecast model for which alpha = 0.25? a. What are the bias, mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE) for the exponential smoothing forecast for time periods 1 through 24? 4. What is the projected demand for the test equipment for time period 25 based upon using a regression forecast model for which the desired confidence level is 95%? a. What are the bias, mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE) for the regression forecast for time periods 1 through 24? 5. Based upon using mean absolute deviation (MAD) as a measure of forecast accuracy, which of the preceding forecast models provides the greatest degree of forecasting accuracy), and which of the preceding forecast models provides the least degree of forecasting accuracy? 2