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Exam (elaborations)

ISQS Final Exam || with 100% Errorless Answers.

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d. Long-range forecasts correct answers Which of the options provided are associated with the effective planning of facility expansion? a. Intermediate-range forecasts b. Make-to-stock operations c. Make-to-order operations d. Long-range forecasts c. Single exponential sm...

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  • August 20, 2024
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ISQS Final Exam || with 100% Errorless Answers.
d.
Long-range forecasts correct answers Which of the options provided are associated with the
effective planning of facility expansion?

a.
Intermediate-range forecasts

b.
Make-to-stock operations

c.
Make-to-order operations

d.
Long-range forecasts

c.
Single exponential smoothing correct answers Choose the forecasting technique used for
forecasting the time series value in a subsequent period by employing a weighted average of
previous time-series values.

A moving average forecast

b.
A grassroots forecast

c.
Single exponential smoothing

d.
Regression analysis

b.
Irregular variation correct answers With data patterns in a time series in mind, which term
describes an explainable, one-time variation?

a.
Cyclical variation

b.
Irregular variation

c.
Seasonal variation

, d.
Random variation

b.
bias correct answers As it pertains to forecasting, _______ references a forecast's tendency to be
larger or smaller than the actual values of a time series on a consistent basis.

a.
variability

b.
bias

c.
trend

d.
fad

b.
The forecast for sales in year 6 is more than 2000 but less than or equal to 2200.

The forecast for sales in year 6 is more than 2000 but less than or equal to 2200. Forecast for
sales in year 6 is (Y6) = 580 + 260(6) = 2140. Excel provides a very simple tool to find the best-
fitting regression model for a time series. correct answers The sales data for high-end staplers at
an office store called Staplers are provided in the following table for the previous 5 years. After
management plotted this data on a chart, it became clear the sales were predictably increasing in
a linear manner. Further, the sales were dependent on time by the function, Y t = 580 + 260t.
Compute the forecasted sales in year 6 by utilizing simple linear regression.
Year Sales
1 950
2 1050
3 1200
4 1650
5 1950

a.
The forecast for sales in year 6 is more than 1800 but less than or equal to 2000.

b.
The forecast for sales in year 6 is more than 2000 but less than or equal to 2200.

c.
The forecast for sales in year 6 is more than 2400 but less than or equal to 2600.

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