A credit union has kept a record of how many new accounts that have been opened over the past fourteen weeks. The branch manager would like to know how many staff members would be required to handle the expected volume of customers for upcoming weeks. The number of new accounts opened at the credit union per week is displayed in the table below:

Weeks (Period X)	New Accounts (Y)
1	19
2	23
3	37
4	28
5	43
6	51
7	29
8	27
9	33
10	47
11	51
12	49
13	55
14	67

1. Develop forecast using the nave, moving average (with 5 periods/week moving average), linear regression, and exponential soothing average (using alpha of 0.1and beta of .02) forecasting methods.
2. For each of the four forecasting methods (naive, moving average, linear regression, and exponential smoothing) explain each of the following:
   1. What is the MSE of the forecast?
   2. What is the MAD of the forecast?
   3. What is the MAPE of the forecast?
   4. Use each forecast to predict how many new accounts will be opened in periods 14, 15, 16 & 17.
   5. How many new accounts will be opened in (period) week 37?
   6. If we assume that one credit union employee can open 20 new accounts per week, how many employees will the credit union branch manager need for periods 14, 15, 16, 17 & 37?
3. Which forecast would you pick as the most accurate? Why? Back up your decision with data.

Note: Develop a graph to visually demonstrate your answers. You can develop your answers using a computer or software package. Show all work through screen shots or hand drawn graphs and charts.