# Problem 35 and BESM Homework

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```					                                Problem 35
MBA 610
Spring 2000

The supervisor of a manufacturing process believed that assembly-line speed
(in feet/minute) affected the number of defective parts found during on-line
inspection. To test this theory, management had the same batch of parts
inspected visually at a variety of line speeds. The following data were
collected:

Line Spd Defect Pts
20       21
20       19
40       15
30       16
60       14
40       17
210      102

a. Develop the estimated regression equation that relates line speed to
the number of defective parts found.

b. Use the equation developed in part (a) to forecast the number of
defective parts found for a line speed of 50 feet per minute.
Demand Forecasting Homework
BESM

A simple exponential smoothing model with smoothing constant equal to 0.4
is used to forecast quarterly demand. Entering quarter 1, the smoothed
average is 30.

(a) Update the model sequentially through each quarter listed below, and
make a forecast for quarter 9. Carry 2 decimal places in all
calculations.

Quarter                           Actual Demand
1                                   28
2                                   33
3                                   31
4                                   29
5                                   28
6                                   36
7                                   30
8                                   24

Show all computations on an attached page. Write the forecast for quarter 9 in the space below:

The forecast for quarter 9 is: ______________

(b) Compute the MAD and BIAS of the forecasting model for quarters 1
through 8.

Show all computations on an attached page. Write the MAD and
BIAS in the spaces below.

BIAS = ___________________

(c) Prove that your forecast for quarter 9 in part (a) above is a
cumulative, weighted average of the initial smoothed average and the
actual demands in quarters 1 through 8.

Show all computations on an attached page. You must show the
weight that is placed on each data point.

```
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