Question 1

The ________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.
A) trend
B) seasonal
C) cyclical
D) irregular

Accepted Answer

The irregular component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

Question 2

The ________ component of a time series measures the fluctuations in a time series due to economic conditions of prosperity and recession with a duration of approximately 2 years or longer.
A) trend
B) seasonal
C) cyclical
D) irregular

Accepted Answer

The cyclical component of a time series measures the fluctuations in a time series due to economic conditions of prosperity and recession with a duration of approximately 2 years or longer.

Question 3

Seasonal variations are periodic patterns in a time series that are repeated over time. For which one of the following time series variables is it not possible to recognize seasonal variations?
A) quarters of the year
B) months of the year
C) days of the week
D) hours of the day
E) years

Accepted Answer

Years are not repeated (periodic); thus, they are not seasonal variations.

Question 4

A major drawback of the aggregate price index is that
A) it does not take into account the fact that some items in the market basket are purchased more frequently than others.
B) it is difficult to compute.
C) it is computed by using the values from a single time series or based on a single product.
D) percentage comparisons cannot be made to the base year.

Accepted Answer

A major drawback of the aggregate price index is that it does not take into account the fact that some items in the market basket are purchased more frequently than others.

Question 5

Suppose that the unadjusted seasonal factor for the month of April is 1.10. The sum of the 12 months' unadjusted seasonal factor values is 12.18. The normalized (adjusted) seasonal factor value for April
A) is larger than 1.1.
B) is smaller than 1.1.
C) is equal to 1.1.
D) cannot be determined with the information provided.

Accepted Answer

12.18/12 = 1.015, which is less than 1.1.

Question 6

The ________ component of a time series consists of erratic and unsystematic fluctuations in the time series data.
A) trend
B) seasonal
C) cyclical
D) irregular

Accepted Answer

The irregular component of a time series consists of erratic and unsystematic fluctuations in the time series data.

Question 7

A sustained long-term change in the level of the variable that is being forecasted per unit of time is
A) a trend.
B) a time series.
C) seasonality.
D) a change due to business cycles.

Accepted Answer

A trend is a sustained long-term change in the level of the variable that is being forecasted per unit of time.

Question 8

Assume that the current date is February 1, 2003. The linear regression model was applied to a monthly time series based on the last 24 months' sales (from January 2000 through December 2002). The following partial computer output summarizes the results.  Determine the predicted sales for this month.
A) 45.9
B) 42.7
C) 44.3
D) 109.1
E) 113.4

Accepted Answer

y₂₆ = 4.3 + 1.6(26) = 45.9

Question 9

A sequence of values of some variable or composite of variables taken at successive, uninterrupted time periods is called a
A) least squares (linear) trend line.
B) moving average.
C) cyclical component.
D) time series.
E) seasonal factor.

Accepted Answer

A sequence of values of some variable or composite of variables taken at successive, uninterrupted time periods is called a time series.

Question 10

When the moving average method is used to estimate the seasonal factors with quarterly sales data, a(n) ________ period moving average is used.
A) 2
B) 3
C) 4
D) 5
E) 8

Accepted Answer

When time is evaluated quarterly, use a 4 period average.

Question 11

Which of the following time series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?
A) dummy variable regression
B) linear trend regression
C) Holt-Winters double exponential smoothing
D) multiplicative Winters method
E) both dummy variable regression and multiplicative Winters method

Accepted Answer

Dummy variable regression and multiplicative Winters method would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Question 12

Assume that the current date is February 1, 2003. The linear regression model was applied to a monthly time series based on the last 24 months' sales (from January 2000 through December 2002). The following partial computer output summarizes the results.  At a significance level of .05, what is the value of the rejection point in testing the slope for significance?
A) 1.717
B) 1.96
C) 2.074
D) 1.645
E) 2.064

Accepted Answer

On the t-chart with a significance level of .05 and 24 − 2 = 22 degrees of freedom, the value of the rejection point is 2.074.

Question 13

In general, the number of dummy variables used to model constant seasonal variation is equal to the number of
A) seasons.
B) seasons minus 1.
C) seasons plus 1.
D) seasons minus 2.
E) seasons divided by two.

Accepted Answer

Dummy variables = seasons − 1

Question 14

The ________ component of a time series reflects the long-run decline or growth in a time series.
A) trend
B) seasonal
C) cyclical
D) irregular

Accepted Answer

The trend component of a time series reflects the long-run decline or growth in a time series.

Question 15

When the magnitude of the seasonal swing does not depend on the level of a time series, we call this ________ variation.
A) increasing seasonal
B) cyclical seasonal
C) constant seasonal
D) decreasing seasonal
E) no seasonal

Accepted Answer

When the magnitude of the seasonal swing does not depend on the level of a time series, we call this constant seasonal variation.

Question 16

Since a(n) ________ index employs the base-period quantities in all succeeding periods, it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.
A) simple
B) aggregate
C) Laspeyres
D) Paasche
E) quantity

Accepted Answer

Since a Laspeyres index employs the base-period quantities in all succeeding periods, it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

Question 17

Which of the following time series forecasting methods would not be used to forecast seasonal data?
A) dummy variable regression
B) simple exponential smoothing
C) time series decomposition
D) multiplicative Winters method

Accepted Answer

We do not use simple exponential smoothing to forecast seasonal data.

Question 18

Those fluctuations that are associated with climate, holidays, and related activities are referred to as ________ variations.
A) trend
B) seasonal
C) cyclical
D) irregular

Accepted Answer

Those fluctuations that are associated with climate, holidays, and related activities are referred to as seasonal variations.

Question 19

A restaurant has been experiencing higher sales during the weekends, compared to the weekdays. Daily restaurant sales patterns for this restaurant over a week are an example of a(n) ________ component of a time series.
A) trend
B) seasonal
C) cyclical
D) irregular

Accepted Answer

Daily restaurant sales patterns for this restaurant over a week are an example of a seasonal component of a time series.

Question 20

In the multiplicative decomposition method, the centered moving averages provide an estimate of
A) trend × seasonal.
B) trend × cycle.
C) seasonal × cycle.
D) trend × irregular.
E) seasonal × irregular.

Accepted Answer

The centered moving averages provide an estimate of trend × cycle in the multiplicative decomposition method.

Quiz 17: Time Series Forecasting and Index Numbers

The ________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

The ________ component of a time series measures the fluctuations in a time series due to economic conditions of prosperity and recession with a duration of approximately 2 years or longer.

Seasonal variations are periodic patterns in a time series that are repeated over time. For which one of the following time series variables is it not possible to recognize seasonal variations?

A major drawback of the aggregate price index is that

Suppose that the unadjusted seasonal factor for the month of April is 1.10. The sum of the 12 months' unadjusted seasonal factor values is 12.18. The normalized (adjusted) seasonal factor value for April

The ________ component of a time series consists of erratic and unsystematic fluctuations in the time series data.

A sustained long-term change in the level of the variable that is being forecasted per unit of time is

A sequence of values of some variable or composite of variables taken at successive, uninterrupted time periods is called a

When the moving average method is used to estimate the seasonal factors with quarterly sales data, a(n) ________ period moving average is used.

Which of the following time series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?

In general, the number of dummy variables used to model constant seasonal variation is equal to the number of

The ________ component of a time series reflects the long-run decline or growth in a time series.

When the magnitude of the seasonal swing does not depend on the level of a time series, we call this ________ variation.

Since a(n) ________ index employs the base-period quantities in all succeeding periods, it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

Which of the following time series forecasting methods would not be used to forecast seasonal data?

Those fluctuations that are associated with climate, holidays, and related activities are referred to as ________ variations.

A restaurant has been experiencing higher sales during the weekends, compared to the weekdays. Daily restaurant sales patterns for this restaurant over a week are an example of a(n) ________ component of a time series.

In the multiplicative decomposition method, the centered moving averages provide an estimate of