1. Axia Pharmaceuticals has a prescription drug for male pattern baldness that has experienced great success. Since being introduced six months ago, sales of this product, IMNotBald, have grown over 50 percent. Last months sales were 60,000 cases of IMNotBald, and Axias management estimates that the trend is increasing at 4,000 cases per month. This months sales were 64,000 cases. In the following calculations, we will use n=1 for all forecasts because forecasts are for the next period, except where noted.

Use =0.3 and =0.2 to calculate a forecast for sales next month.

If sales in month 2 are actually 63,000, calculated the forecast for month 3.

If sales in month 3 are actually 60,800, calculate the forecast for month 4.

Using the information above, develop forecasts for months 5 through 13.

Month	Demand	Forecast (F)	A	T
3	60,500
4	69,000
5	67,500
6	69,000
7	77,000
8	78,000
9	77,500
10	86,000
11	81,000
12	82,500
13
14
15

Using the data in the table, develop forecasts for months 14 and 15.

2. An ice cream manufacturer wants to predict monthly demand for all flavors of its ice cream. The data consist of both trend and seasonal components. The forecast with trend component is calculated using the formula F_t= 8,600 + 26t. Use the data in the table below to develop seasonal indices for each month. Use this information to forecast demand for July and August of year 4.

	Sales	Sales	Sales
	Year 1	Year 2	Year 3
January	6000	6200	6300
February	6500	6400	7200
March	6300	6500	6800
April	8500	8700	9300
May	9000	9600	10000
June	9700	9900	10500
July	10300	11000	10800
August	11400	11700	12400
September	9300	9700	9500
October	8400	8900	9000
November	5500	5700	5800
December	5100	5300	5600
Average	8000	8300	8600

3. The table below provides demand for the past 6 weeks and the corresponding forecast for the total cabinet sales at Quality Cabinets. Calculate CFE, MSE, , and MAD for this set of forecasts.

Week	Demand	Forecast
1	300	290
2	320	298
3	290	310
4	345	295
5	325	317
6	310	335
7		318