Question 1

Gradual shifting of a time series to relatively higher or lower values over a long period of time is called

Accepted Answer

A)  periodicity. 
B)  cycles. 
C)  seasonality. 
D)  trend. 
A)  periodicity. 
B)  cycles. 
C)  seasonality. 
D)  trend. D

Question 2

Monthly sales at a coffee shop have been analyzed. The seasonal index values are
   and the trend line is 74123 + 26.9(t). Assume there is no cyclical component and forecast sales for year 8 (months 97 - 108).

Accepted Answer

The answer of Monthly sales at a coffee shop have...

Question 3

One measure of the accuracy of a forecasting model is the

Accepted Answer

A)  smoothing constant 
B)  linear trend 
C)  mean absolute error 
D)  seasonal index 
A)  smoothing constant 
B)  linear trend 
C)  mean absolute error 
D)  seasonal index C

Question 4

If the random variability in a time series is great, a high $\alpha$ value should be used to exponentially smooth out the fluctuations.

Accepted Answer

A) True 
 B)False

Question 5

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

Accepted Answer

A)  MSE 
B)  MAPE 
C)  MAE 
D)  ME 
A)  MSE 
B)  MAPE 
C)  MAE 
D)  ME

Question 6

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

Accepted Answer

A) True 
 B)False

Question 7

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

Accepted Answer

A) True 
 B)False

Question 8

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

Accepted Answer

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

Question 9

All of the following are true about qualitative forecasting methods except

Accepted Answer

A)  They generally involve the use of expert judgment to develop forecasts. 
B)  They assume the pattern of the past will continue into the future. 
C)  They are appropriate when past data on the variable being forecast are not applicable. 
D)  They are appropriate when past data on the variable being forecast are not available. 
A)  They generally involve the use of expert judgment to develop forecasts. 
B)  They assume the pattern of the past will continue into the future. 
C)  They are appropriate when past data on the variable being forecast are not applicable. 
D)  They are appropriate when past data on the variable being forecast are not available.

Question 10

Which of the following exponential smoothing constant values puts the same weight on the most recent time series value as does a 5-period moving average?

Accepted Answer

A)  $\alpha$ = .2 
B)  $\alpha$= .25 
C)  $\alpha$= .75 
D) $\alpha$ = .8 
A)  $\alpha$ = .2 
B)  $\alpha$= .25 
C)  $\alpha$= .75 
D) $\alpha$ = .8

Question 11

Forecast errors

Accepted Answer

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 
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 12

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.

Accepted Answer

A) True 
 B)False

Question 13

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

Accepted Answer

A) True 
 B)False

Question 14

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

Accepted Answer

A) True 
 B)False

Question 15

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

Accepted Answer

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

Question 16

If data for a time series analysis is collected on an annual basis only, which pattern does not need to be considered?

Accepted Answer

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

Question 17

Time series data can exhibit seasonal patterns of less than one month in duration.

Accepted Answer

A) True 
 B)False

Question 18

If a time series has a significant trend pattern, then one should not use a moving average to forecast.

Accepted Answer

A) True 
 B)False

Question 19

An alpha ($\alpha$) value of .2 will cause an exponential smoothing forecast to react more quickly to a sudden drop in demand than will an $\alpha$equal to .4.

Accepted Answer

A) True 
 B)False

Question 20

Seasonal patterns

Accepted Answer

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

Gradual shifting of a time series to relatively higher or lower values over a long period of time is called

Monthly sales at a coffee shop have been analyzed. The seasonal index values are and the trend line is 74123 + 26.9(t). Assume there is no cyclical component and forecast sales for year 8 (months 97 - 108).

One measure of the accuracy of a forecasting model is the

If the random variability in a time series is great, a high $\alpha$ value should be used to exponentially smooth out the fluctuations.

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

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

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

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

All of the following are true about qualitative forecasting methods except

Which of the following exponential smoothing constant values puts the same weight on the most recent time series value as does a 5-period moving average?

Forecast errors

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.

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

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

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

If data for a time series analysis is collected on an annual basis only, which pattern does not need to be considered?

Time series data can exhibit seasonal patterns of less than one month in duration.

If a time series has a significant trend pattern, then one should not use a moving average to forecast.

An alpha ( $\alpha$ ) value of .2 will cause an exponential smoothing forecast to react more quickly to a sudden drop in demand than will an $\alpha$ equal to .4.

Seasonal patterns

Introduction

An Introduction to Linear Programming

Linear Programming: Sensitivity Analysis and Interpretation of Solution

Linear Programming Applications in Marketing, Finance, and Operations Management

Advanced Linear Programming Applications

Distribution and Network Models

Integer Linear Programming

Nonlinear Optimization Models

Project Scheduling: Pertcpm

Inventory Models

Waiting Line Models

Simulation

Decision Analysis

Multicriteria Decisions

Markov Processes

Filters

Exam 15: Forecasting

Gradual shifting of a time series to relatively higher or lower values over a long period of time is called

Monthly sales at a coffee shop have been analyzed. The seasonal index values are and the trend line is 74123 + 26.9(t). Assume there is no cyclical component and forecast sales for year 8 (months 97 - 108).

One measure of the accuracy of a forecasting model is the

If the random variability in a time series is great, a high α\alphaα value should be used to exponentially smooth out the fluctuations.

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

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

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

To select a value for α\alphaα for exponential smoothing

All of the following are true about qualitative forecasting methods except

Which of the following exponential smoothing constant values puts the same weight on the most recent time series value as does a 5-period moving average?

Forecast errors

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.

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

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

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

If data for a time series analysis is collected on an annual basis only, which pattern does not need to be considered?

Time series data can exhibit seasonal patterns of less than one month in duration.

If a time series has a significant trend pattern, then one should not use a moving average to forecast.

An alpha ( α\alphaα ) value of .2 will cause an exponential smoothing forecast to react more quickly to a sudden drop in demand than will an α\alphaα equal to .4.

Seasonal patterns

Introduction

An Introduction to Linear Programming

Linear Programming: Sensitivity Analysis and Interpretation of Solution

Linear Programming Applications in Marketing, Finance, and Operations Management

Advanced Linear Programming Applications

Distribution and Network Models

Integer Linear Programming

Nonlinear Optimization Models

Project Scheduling: Pertcpm

Inventory Models

Waiting Line Models

Simulation

Decision Analysis

Multicriteria Decisions

Markov Processes

Filters

If the random variability in a time series is great, a high $\alpha$ value should be used to exponentially smooth out the fluctuations.

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

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

An alpha ( $\alpha$ ) value of .2 will cause an exponential smoothing forecast to react more quickly to a sudden drop in demand than will an $\alpha$ equal to .4.