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BA 252
Dr. Campbell
SAMPLES I
1.
The demand for months 14 is as follows: 90, 85, 87, 83.
a) Forecast demand for month 5 using: a 3period moving average, a 2period weighted moving
average with weights of 0.7 and 0.3, and exponential smoothing with
α
=0.3 (use 85 as the old
forecast for period 4).
b) Suppose the actual demand for month 5 is 82. Forecast demand for month 6 using: a 3period
simple moving average, a 2period weighted moving average with weights of 0.7 and 0.3, and
exponential smoothing with
α
=0.3.
c) If the demand for month 6 was 80, determine the mean absolute deviation (MAD), mean
squared error (MSE) and mean absolute percentage error (MAPE) for the three period moving
average for months 5 and 6.
2. a) Calculate the best fitting line using linear regression to forecast demand using the data for
four periods of demand and number of salespeople below.
number of salespeople
14
16
12
15
demand
40
50
20
42
b) If there are 17 salespeople in the next period, what is the forecast for demand?
c) Graph the four data points and the linear regression line.
3. The following statement defines a set of decision variables for a linear programming problem:
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This note was uploaded on 02/15/2012 for the course BA 252 taught by Professor Jamescampbell during the Winter '03 term at UMSL.
 Winter '03
 JamesCampbell

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