Deck 16: Time Series Forecasting

Question 1

Simple exponential forecasting method would not be used to forecast seasonal data.

Answer 1

True

Question 2

Simple moving average method is primarily useful in determining the impact of trend on a time series.

Answer 2

False

Question 3

Dummy variables are used to model increasing seasonal variation.

Answer 3

False

Question 4

When deseasonalizing a time series observation the actual time series observation is divided by its seasonal factor.

Question 5

While a simple index is calculated by using the values of one time series,an aggregate index is computed based on the accumulated values of more than one time series.

Question 6

A univariate time series model is used to predict future values of a time series based only upon past values of a time series.

Question 7

Removing the seasonal affect by dividing the actual time series observation by the estimated seasonal factor associated with the time series observation is called deseasonalization.

Question 8

The smoothing constant is a number that determines how much weight it is attached to each observation.

Question 9

Simple exponential smoothing is an appropriate method for prediction purposes when there is a significant trend present in a time series data.

Question 10

Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series.

Question 11

Trend refers to a long-run upward or downward movement of a time series over a period of time.

Question 12

A positive autocorrelation implies that negative error terms will be followed by negative error terms.

Question 13

When using moving averages to estimate the seasonal factors,we need to compute the centered moving average if there are odd number of seasons.

Question 14

The forecaster who uses MSD (mean squared deviations)to measure the effectiveness of forecasting methods would prefer method 1 that results in several smaller forecast errors to method 2 that results in one large forecast error equal to the sum of the absolute values of several small forecast errors given by method 1.

Question 15

Time series decomposition method would not be used to forecast seasonal data.

Question 16

Holt - Winter's double exponential smoothing would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Question 17

When a forecaster uses multiplicative decomposition model or time series regression model she or he assumes that the time series components are changing over time.

Question 18

Exponential smoothing is a forecasting method that applies equal weights to the time series observations.

Question 19

Paasche index more accurately provides a year-to-year comparison of the annual cost of selected products in the market-basket than Laspeyres index.

Question 20

Dummy variable regression would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Question 21

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

Question 22

When a forecaster uses the _________________ method she or he assumes that the time series components are changing quickly over time.

A)Time series regression
B)Simple exponential smoothing
C)Box and Jenkins
D)Multiplicative decomposition

Question 23

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

Question 24

The no trend time series model is given by

A)TR_t = B₀ + B_1t
B)TR_t = B₀
C)TR_t = B₀ + B_1t + B_2t²
D)TR_t = B₀ + B_1ln(t)

Question 25

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

A)Trend
B)Seasonal
C)Cyclical
D)Irregular

Question 26

All of the following are forecasting methods except

A)Holt-Winters' double exponential smoothing
B)Box and Jenkins
C)Time series regression
D)MAD autocorrelation

Question 27

If the errors produced by a forecasting method for 3 observations are + 3,+ 3 and - 3,then what is the mean absolute deviation?

A)9
B)0
C)3
D)-3

Question 28

_________ component of time series refers to the erratic time-series movement that follow no recognizable or regular pattern.

A)Trend
B)Seasonal
C)Cyclical
D)Irregular

Question 29

In the Durbin-Watson test,if the calculated d-statistic is greater than the upper value of the d-statistic,then

A)We do not reject H₀ which says the error terms are not autocorrelated
B)We do reject H₀ which says the error terms are not autocorrelated
C)The test is inconclusive
D)We do reject H₀,which says the error terms are positively or negatively autocorrelated

Question 30

Which of the following is not a component of time series?

A)Trend
B)Seasonal
C)Cyclical
D)Irregular
E)Smoothing constant

Question 31

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

A)Trend
B)Seasonal
C)Cyclical
D)Irregular

Question 32

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.

Question 33

When the moving average method is used to estimate the seasonal factors with quarterly sales data,a ______ period moving average is used.

A)2
B)3
C)4
D)5
E)8

Question 34

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

A)Trend
B)Seasonal
C)Cyclical
D)Irregular

Question 35

If the errors produced by a forecasting method for 3 observations are + 3,+ 3 and - 3,then what is the mean squared error?

A)9
B)0
C)3
D)-3
E)2

Question 36

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 averages
C)Cyclical component
D)Time series
E)Seasonal factor

Question 37

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 is

A)Larger than 1.1
B)Smaller than 1.1
C)Equal to 1.1
D)Cannot be determined with the information provided.

Question 38

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

A)Trend
B)Seasonal
C)Cyclical
D)Irregular

Question 39

When a forecaster uses the ______________ method she or he assumes that the time series components are changing slowly over time.

A)Time series regression
B)Exponential smoothing
C)Box and Jenkins
D)Multiplicative decomposition

Question 40

If the errors produced by a forecasting method for 3 observations are -1,-2 and -6,then what is the mean squared error (deviation)?

A)9
B)-9
C)3
D)13.67

Question 41

Based on the information given in the table above,we can conclude that in general the forecasting method is:

A)Underestimating demand
B)Overestimating demand
C)We cannot determine whether the predictions based on this method's results in underestimation or overestimation of demand.

Question 42

Based on the information given in the table above,what is the average forecast error?

A)1.3333
B)1.6667
C)2.5
D)3.3333
E)4.5

Question 43

Use this equation to forecast the demand for this product and calculate the MSD.

A)MSD = 6
B)MSD = 3.3333
C)MSD = 7.0
D)MSD = 2
E)MSD = 2.4

Question 44

Based on the information given in the table above,what is the MAD?

A)1.3333
B)1.6667
C)2.5
D)3.3333
E)4.5

Question 45

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

A)Trend x seasonal
B)Trend x cycle
C)Seasonal x cycle
D)Trend x irregular
E)Seasonal x irregular

Question 46

Assume that the current date is February 1,2003.The linear regression model was applied to a monthly time series data 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

Question 47

Seasonal variations are periodic patterns in a time series that are repeated over time.For which one of the following time series variables,it is 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

Question 48

As you probably know,in a given week,the NYSE (New York Stock Exchange)is generally open from Monday through Friday.If we wanted to use multiple regression method with dummy variables to study the impact of the day of the week on stock market performance,we would need ____ dummy variables.

A)5
B)52
C)4
D)3
E)365

Question 49

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.What are the forecast errors for the 5^th and 6^th years?

A)0,-3
B)0,+ 3
C)+ 2,+ 5
D)-2,-5
E)-1,-4

Question 50

Use this equation to forecast the demand for this product and calculate the MAD.

A)MAD = 1.333
B)MAD = 1.6
C)MAD = 2.0
D)MAD = 2.333
E)MAD = 2.5

Question 51

Assume that the current date is February 1,2003.The linear regression model was applied to a monthly time series data 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

Question 52

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 Winter's double exponential smoothing
D)Multiplicative Winter's method
E)Both A and D

Question 53

Since the ____________ 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

Question 54

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 Winter's method

Question 55

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

Question 56

When there is first-order autocorrelation,the error term in period t is related to the error term in period _____.

A)t
B)t + 1
C)t - 1
D)t - 2

Question 57

Based on the information given in the table above,what is the MSD?

A)1.3333
B)1.6667
C)2.5
D)3.3333
E)4.5

Question 58

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

Question 59

When there is _______________ seasonal variation,the magnitude of the seasonal swing does not depend on the level of the time series.

A)cyclical
B)constant
C)irregular
D)increasing

Question 60

When using simple exponential smoothing,the value of the smoothing constant $\alpha$ cannot be:

A)Negative
B)Greater than zero
C)Greater than 1
D).99
E)Both A and C

Question 61

The upward or downward movement that characterizes a time series over a period of time is referred to as ____.

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

Question 62

A forecasting method that weights recent observations more heavily is called ____.

A)time series analysis
B)first-order autocorrelation
C)multiplicative decomposition
D)exponential smoothing

Question 63

The purpose behind moving averages and centered moving averages is to eliminate _________________.

A)constant variation
B)cyclical variation
C)seasonal variation
D)regular variation

Question 64

The basic difference between MAD and MSE is that MSE,unlike MAD,penalizes a forecasting technique much more for _____ errors than for _____ errors.

A)large,small
B)small,large
C)small,zero
D)zero,large

Question 65

_______________ index is most useful if the base quantities provide a reasonable representation of consumption patterns in succeeding time periods.

A)Paasche
B)Weighted aggregate
C)Laspeyres
D)Cyclical (seasonal)

Question 66

A positive autocorrelation implies that negative error terms will be followed by _________ error terms.

A)negative
B)positive
C)either negative or positive
D)irregular

Question 67

If a time series exhibits increasing seasonal variation,one approach is to first use a ______________ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_________ variables can be used to model the time series with constant seasonal variation.

A)autocorrelation,dummy
B)fractional power,dummy
C)fractional power,constant
D)autocorrelation,constant

Question 68

When preparing a price index based on multiple products,if the price of each product is weighted by the quantity of the product purchased in a given period of time,the resulting index is called ___________ price index.

A)Paasche
B)Weighted aggregate
C)Laspeyres
D)Cyclical (seasonal)

Question 69

In the multiplicative decomposition method,the centered moving averages provide an estimate of trend x _____.

A)index
B)cycle
C)seasonal
D)irregular

Question 70

The Laspeyres index and the Paasche index are both examples of _________ aggregate price indexes.

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

Question 71

The _____ test is a test for first-order positive autocorrelation.

A)Durbin-Watson
B)MSD
C)MAD
D)Multiplicative Winters

Question 72

A simple index is computed by using the values of one time series,while the _______ index is based on a "market basket" consisting of more than one time series.

A)weighted
B)aggregate
C)cyclical
D)trend

Question 73

Holt - Winters double exponential smoothing method is used to forecast time series data with ________.

A)autocorrelation
B)linear trend
C)cyclical patterns
D)moving averages

Question 74

The Durbin-Watson statistic is used to detect ____.

A)first-order autocorrelation
B)exponential smoothing
C)multiplicative decomposing
D)irregular variation

Question 75

When deseasonalizing time series observation,we divide the actual time series observation by its __________.

A)irregular factor
B)cyclical factor
C)seasonal factor
D)weighted aggregate factor

Question 76

Weighting in exponential smoothing is accomplished by the use of ____.

A)first-order autocorrelation
B)smoothing constants
C)Durbin-Watson
D)multiplicative decomposing

Question 77

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____ time period and by multiplying this ratio by 100.

A)base
B)final
C)current
D)shortest

Question 78

Periodic patterns in time series that repeat themselves within a calendar year or less are referred to as ____.

A)constant variations
B)cyclical variations
C)seasonal variations
D)regular variations

Question 79

When using simple exponential smoothing,the more recent the time series observation,the _________ its corresponding weight.

A)larger
B)smaller
C)irregular
D)cyclical

Question 80

The recurring up-and-down movement of a time series around trend levels that last more than one calendar year is called ____.

A)constant variation
B)cyclical variation
C)seasonal variation
D)irregular variation