$(2$ pts$)$ Using the provided data set, compute the Na$$ve$,$ Two$-$period Moving Average, Three$-$period

Moving Average, Two$-$period Weighted Moving Average with weights $(0\mathrm{.}6,0\mathrm{.}4),$ Three$-$period

Weighted Moving Average with weights $(0\mathrm{.}5,0\mathrm{.}3,0\mathrm{.}2),$ Linear Trend, and Exponential Smoothing

with alpha$=0\mathrm{.}4$ and alpha$=0\mathrm{.}8$ forecasts for sales.

$2.(0\mathrm{.}5$ pts$)$ Compute the best value of alpha for the Exponential Smoothing method that minimizes

the Root Mean Square Error $($RMSE$).$

$3.(1$ pt$)$ Identify the best Weighted Moving Average $($WMA$)$ method that minimizes the Root Mean

Square Error $($RMSE$)$ and compute the weights associated with that method. For this question, you

should consider all the WMA methods up to $12$ periods.

$4.(1$ pt$)$ Compare the forecasting methods discussed in Questions $1-3$ in order to identify the best

forecasting method among them. For this question, compute MAE, RMSE, and MAPE under these

methods and compare the corresponding values. What is the best forecasting method?

Hint: You don$$t have to consider methods that are redundant in your comparison.

$5.(1\mathrm{.}5$ pts$)$ Do you observe trends or seasonality in this data set? If yes, explain how you would handle

trend and$/$or seasonality. For this question, you should forecast the demand for the next $12$ months

incorporating any trend and$/$or seasonality that exists in the data set.