Question 1

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

Accepted Answer

A) True 
 B)False  True

Question 2

All of the following are true about a cyclical pattern except

Accepted Answer

A) It is often due to multiyear business cycles. 
B) It is often combined with long-term trend patterns and called trend-cycle patterns. 
C) It usually is easier to forecast than a seasonal pattern due to less variability. 
D) It is an alternating sequence of data points above and below the trend line. 
A) It is often due to multiyear business cycles. 
B) It is often combined with long-term trend patterns and called trend-cycle patterns. 
C) It usually is easier to forecast than a seasonal pattern due to less variability. 
D) It is an alternating sequence of data points above and below the trend line. C

Question 3

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

Accepted Answer

A) True 
 B)False  True

Question 4

All of the following are true about a stationary time series except

Accepted Answer

A) Its statistical properties are independent of time. 
B) A plot of the series will always exhibit a horizontal pattern. 
C) The process generating the data has a constant mean 
D) There is no variability in the time series over time. 
A) Its statistical properties are independent of time. 
B) A plot of the series will always exhibit a horizontal pattern. 
C) The process generating the data has a constant mean 
D) There is no variability in the time series over time.

Question 5

Explain and contrast three measures of forecast accuracy.​

Accepted Answer

There are several measures of forecast a

Question 6

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 7

​In situations where you need to compare forecasting methods for different time periods,relative measures such as mean absolute error (MAE)are preferred.

Accepted Answer

A) True 
 B)False

Question 8

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

Accepted Answer

A) True 
 B)False

Question 9

Discuss the effects of using a small smoothing constant value and when it is most appropriate to use.Then,do the
same for a large smoothing constant value.​

Accepted Answer

Using a small smoothing constant value i

Question 10

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 11

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

Accepted Answer

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

Question 12

If the random variability in a time series is great and exponential smoothing is being used to forecast,then a high alpha (α)value should be used.

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

All of the following are true about time series methods except

Accepted Answer

A) They discover a pattern in historical data and project it into the future. 
B) They involve the use of expert judgment to develop forecasts. 
C) They assume that the pattern of the past will continue into the future. 
D) Their forecasts are based solely on past values of the variable or past forecast errors. 
A) They discover a pattern in historical data and project it into the future. 
B) They involve the use of expert judgment to develop forecasts. 
C) They assume that the pattern of the past will continue into the future. 
D) Their forecasts are based solely on past values of the variable or past forecast errors.

Question 15

Trend in a time series must be linear.

Accepted Answer

A) True 
 B)False

Question 16

How can error measures be used to determine the number of periods to use in a moving average? What are you
assuming about the future when you make this choice?​

Accepted Answer

Error measures can be used to determine

Question 17

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

Accepted Answer

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

Question 18

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 19

​When using a moving average of order k to forecast,a small value for k is preferred if only the most recent values of the time series are considered relevant.

Accepted Answer

A) True 
 B)False

Question 20

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

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

All of the following are true about a cyclical pattern except

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

All of the following are true about a stationary time series except

Explain and contrast three measures of forecast accuracy.

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.

In situations where you need to compare forecasting methods for different time periods,relative measures such as mean absolute error (MAE)are preferred.

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

Discuss the effects of using a small smoothing constant value and when it is most appropriate to use.Then,do the same for a large smoothing constant value.

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

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

If the random variability in a time series is great and exponential smoothing is being used to forecast,then a high alpha (α)value should be used.

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

All of the following are true about time series methods except

Trend in a time series must be linear.

How can error measures be used to determine the number of periods to use in a moving average? What are you assuming about the future when you make this choice?

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

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

When using a moving average of order k to forecast,a small value for k is preferred if only the most recent values of the time series are considered relevant.

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

Introduction

Introduction to Probability

Probability Distributions

Decision Analysis

Utility Game Theory

Intro to Linear Programming

LP Sensitivity Analysis

LP Applications

Distribution Network Models

Integer Linear Programming

Advanced Optimization Applications

Project Scheduling

Inventory Models

Waiting Line Models

Simulation

Markov Processes

Filters

Exam 6: Time Series Analysis Forecasting

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

All of the following are true about a cyclical pattern except

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

All of the following are true about a stationary time series except

Explain and contrast three measures of forecast accuracy.​

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.

​In situations where you need to compare forecasting methods for different time periods,relative measures such as mean absolute error (MAE)are preferred.

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

Discuss the effects of using a small smoothing constant value and when it is most appropriate to use.Then,do the same for a large smoothing constant value.​

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

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

If the random variability in a time series is great and exponential smoothing is being used to forecast,then a high alpha (α)value should be used.

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

All of the following are true about time series methods except

Trend in a time series must be linear.

How can error measures be used to determine the number of periods to use in a moving average? What are you assuming about the future when you make this choice?​

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

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

​When using a moving average of order k to forecast,a small value for k is preferred if only the most recent values of the time series are considered relevant.

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

Introduction

Introduction to Probability

Probability Distributions

Decision Analysis

Utility Game Theory

Intro to Linear Programming

LP Sensitivity Analysis

LP Applications

Distribution Network Models

Integer Linear Programming

Advanced Optimization Applications

Project Scheduling

Inventory Models

Waiting Line Models

Simulation

Markov Processes

Filters

Explain and contrast three measures of forecast accuracy.

In situations where you need to compare forecasting methods for different time periods,relative measures such as mean absolute error (MAE)are preferred.

Discuss the effects of using a small smoothing constant value and when it is most appropriate to use.Then,do the same for a large smoothing constant value.

How can error measures be used to determine the number of periods to use in a moving average? What are you assuming about the future when you make this choice?

When using a moving average of order k to forecast,a small value for k is preferred if only the most recent values of the time series are considered relevant.