4.2 a) Plot the above data on a graph. Do you observe any trend, cycles, or random variations? b) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average. Plot your forecast on the same graph as the original data. c) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average with weights of .1, .3, and .6, using .6 for the most recent year. Plot this forecast on the same graph. 4.6 MONTH January February March April May June July August September October November December SALES 20 21 15 14 13 16 17 18 20 20 21 23 a) Plot the monthly sales data. b) Forecast January sales using each of the following: i) Naive method. ii) A 3-month moving average. iii) A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. iv) Exponential smoothing using an = .3 and a September forecast of 18. v) A trend projection. c) With the data given, which method would allow you to forecast next March's sales? 4.9 Lenovo uses the ZX-81 chip in some of its laptop computers. The prices for the chip during the past 12 months were as follows: a) Use a 2-month moving average on all the data and plot the averages and the prices. b) Use a 3-month moving average and add the 3-month plot to the graph created in part (a). c) Which is better (using the mean absolute deviation): the 2-month average or the 3-month average? d) Compute the forecasts for each month using exponential smoothing, with an initial forecast for January of $1.80. Use = .1, then = .3, and finally = .5. Using MAD, which a is the best