Deck 15: Forecasting

Question 1

To select a value for $\alpha$ for exponential smoothing

A)use a small $\alpha$ when the series varies substantially.
B)use a large $\alpha$ when the series has little random variability.
C)use any value between 0 and 1
D)All of the alternatives are true.

Answer 1

All of the alternatives are true.

Question 2

Time series methods base forecasts only on past values of the variables.

Answer 2

True

Question 3

Using exponential smoothing, the demand forecast for time period 10 equals the demand forecast for time period 9 plus

A) $\alpha$ times (the demand forecast for time period 8)
B) $\alpha$ times (the error in the demand forecast for time period 9)
C) $\alpha$ times (the observed demand in time period 9)
D) $\alpha$ times (the demand forecast for time period 9)

Answer 3

$\alpha$ times (the error in the demand forecast for time period 9)

Question 4

One measure of the accuracy of a forecasting model is the

A)smoothing constant
B)trend component
C)mean absolute deviation
D)seasonal index

Question 5

A qualitative forecasting method that obtains forecasts through "group consensus" is known as the

A)Autoregressive model
B)Delphi approach
C)mean absolute deviation
D)None of these alternatives is correct.

Question 6

The trend component is easy to identify by using

A)moving averages
B)exponential smoothing
C)regression analysis
D)the Delphi approach

Question 7

Gradual shifting of a time series over a long period of time is called

A)periodicity.
B)cycle.
C)regression.
D)trend.

Question 8

Which of the following is a qualitative forecasting method?

A)trend projection
B)time series method
C)smoothing method
D)Delphi method

Question 9

Causal models

A)should avoid the use of regression analysis.
B)attempt to explain a time series' behavior.
C)do not use time series data.
D)All of the alternatives are true.

Question 10

Seasonal components

A)cannot be predicted.
B)are regular repeated patterns.
C)are long runs of observations above or below the trend line.
D)reflect a shift in the series over time.

Question 11

Linear trend is calculated as T_t = 28.5 + .75t.The trend projection for period 15 is

A)11.25
B)28.50
C)39.75
D)44.25

Question 12

Time series methods

A)discover a pattern in historical data and project it into the future.
B)include cause-effect relationships.
C)are useful when historical information is not available.
D)All of the alternatives are true.

Question 13

The multiplicative model

A)uses centered moving averages to smooth the trend fluctuations.
B)removes trend before isolating the seasonal components.
C)deseasonalizes a time series by dividing the values by the appropriate seasonal index.
D)provides a unique seasonal index for each observation of the time series.

Question 14

Short-term, unanticipated, and nonrecurring factors in a time series provide the random variability known as

A)uncertainty.
B)the forecast error.
C)the residuals.
D)the irregular component.

Question 15

Which of the following forecasting methods puts the least weight on the most recent time series value?

A)exponential smoothing with $\alpha$ = .3
B)exponential smoothing with $\alpha$ = .2
C)moving average using the most recent 4 periods
D)moving average using the most recent 3 periods

Question 16

The forecasting method that is appropriate when the time series has no significant trend, cyclical, or seasonal effect is

A)moving averages
B)mean squared error
C)mean average deviation
D)qualitative forecasting methods

Question 17

Quantitative forecasting methods do not require that patterns from the past will necessarily continue in the future.

Question 18

Forecast errors

A)are the difference in successive values of a time series
B)are the differences between actual and forecast values
C)should all be nonnegative
D)should be summed to judge the goodness of a forecasting model

Question 19

The focus of smoothing methods is to smooth

A)the irregular component.
B)wide seasonal variations.
C)significant trend effects.
D)long range forecasts.

Question 20

If data for a time series analysis is collected on an annual basis only, which component may be ignored?

A)trend
B)seasonal
C)cyclical
D)irregular

Question 21

If the random variability in a time series is great, a high SYMBOL 97 \f "Symbol" value should be used to exponentially smooth out the fluctuations.

Question 22

The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series.

Question 23

Seasonal components with values above 1.00 indicate actual values below the trend line.

Question 24

With fewer periods in a moving average, it will take longer to adjust to a new level of demand.

Question 25

All quarterly time series contain seasonality.

Question 26

Qualitative forecasting techniques should be applied in situations where time series data exists, but where conditions are expected to change.

Question 27

For a multiplicative time series model, the sum of the seasonal indexes should equal the number of seasons.

Question 28

Any recurring sequence of points above and below the trend line lasting less than one year can be attributed to the cyclical component of the time series.

Question 29

The mean squared error is influenced much more by large forecast errors than by small errors.

Question 30

To make period-to-period comparisons more meaningful and identify trend, the time series should be deseasonalized.

Question 31

Trend in a time series must be linear.

Question 32

Smoothing methods are more appropriate for a stable time series than when significant trend and/or seasonal variation are present.

Question 33

A four-period moving average forecast for period 10 would be found by averaging the values from periods 10, 9, 8, and 7.

Question 34

A time series model with a seasonal component will always involve quarterly data.