Question 1

Which of the following statements is the objective of the moving averages and exponential smoothing methods?

Accepted Answer

A) To maximize forecast accuracy measures 
B) To smooth out random fluctuations in the time series 
C) To characterize the variable fluctuations by an exponential equation 
D) To transform a nonstationary time series into a stationary series 
A) To maximize forecast accuracy measures 
B) To smooth out random fluctuations in the time series 
C) To characterize the variable fluctuations by an exponential equation 
D) To transform a nonstationary time series into a stationary series

Question 2

Which of the following is not true of a stationary time series?

Accepted Answer

A) The process generating the data has a constant mean. 
B) The time series plot is a straight line. 
C) The statistical properties are independent of time. 
D) The variability is constant over time. 
A) The process generating the data has a constant mean. 
B) The time series plot is a straight line. 
C) The statistical properties are independent of time. 
D) The variability is constant over time.

Question 3

The process of __________ might be used to determine the value of the smoothing constant that minimizes the mean squared error.

Accepted Answer

A) quantization 
B) nonlinear optimization 
C) clustering 
D) curve fitting 
A) quantization 
B) nonlinear optimization 
C) clustering 
D) curve fitting

Question 4

An exponential trend pattern occurs when

Accepted Answer

A) the amount of increase between periods in the value of the variable is constant. 
B) the percentage change between periods in the value of the variable is relatively constant. 
C) there is a no relationship between the time series variable and time. 
D) there are random fluctuations in the variable value with time. 
A) the amount of increase between periods in the value of the variable is constant. 
B) the percentage change between periods in the value of the variable is relatively constant. 
C) there is a no relationship between the time series variable and time. 
D) there are random fluctuations in the variable value with time.

Question 5

A time series plot of a period of time (quarterly) versus quarterly sales (in $1,000s) is shown below. Which of the following data patterns best describes the scenario shown?

Accepted Answer

A) Linear trend and cyclical pattern 
B) Linear trend and horizontal pattern 
C) Seasonal and cyclical patterns 
D) Seasonal pattern and linear trend 
A) Linear trend and cyclical pattern 
B) Linear trend and horizontal pattern 
C) Seasonal and cyclical patterns 
D) Seasonal pattern and linear trend

Question 6

A time series that shows a recurring pattern over one year or less is said to follow a

Accepted Answer

A) horizontal pattern. 
B) stationary pattern. 
C) cyclical pattern. 
D) seasonal pattern. 
A) horizontal pattern. 
B) stationary pattern. 
C) cyclical pattern. 
D) seasonal pattern.

Question 7

In the moving averages method, the order k determines the

Accepted Answer

A) error tolerance. 
B) compensation for forecasting error. 
C) number of time series values under consideration. 
D) number of samples in each unit time period. 
A) error tolerance. 
B) compensation for forecasting error. 
C) number of time series values under consideration. 
D) number of samples in each unit time period.

Question 8

A positive forecast error indicates that the forecasting method ________ the dependent variable.

Accepted Answer

A) overestimated 
B) underestimated 
C) accurately estimated 
D) closely approximated 
A) overestimated 
B) underestimated 
C) accurately estimated 
D) closely approximated

Question 9

The moving averages method refers to a forecasting method that

Accepted Answer

A) is used when considerable trend, cyclical, or seasonal effects are present. 
B) uses regression relationship based on past time series values to predict the future time series values. 
C) relates a time series to other variables that are believed to explain or cause its behavior. 
D) uses the average of the most recent data values in the time series as the forecast for the next period. 
A) is used when considerable trend, cyclical, or seasonal effects are present. 
B) uses regression relationship based on past time series values to predict the future time series values. 
C) relates a time series to other variables that are believed to explain or cause its behavior. 
D) uses the average of the most recent data values in the time series as the forecast for the next period.

Question 10

A time series plot of a period of time (in weeks) versus sales (in 1,000's of gallons) is shown below. Which of the following data patterns best describes the scenario shown?

Accepted Answer

A) Time series with a linear trend pattern 
B) Time series with a nonlinear trend pattern 
C) Time series with no pattern 
D) Time series with a horizontal pattern 
A) Time series with a linear trend pattern 
B) Time series with a nonlinear trend pattern 
C) Time series with no pattern 
D) Time series with a horizontal pattern

Question 11

The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by

Accepted Answer

A) determining how well a particular forecasting method is able to reproduce the time series data that are already available. 
B) using the current value to estimate how well the model generates previous values correctly. 
C) predicting the future values and wait for a pre-defined time period to examine how accurate the predictions were. 
D) adjusting the scale of the data. 
A) determining how well a particular forecasting method is able to reproduce the time series data that are already available. 
B) using the current value to estimate how well the model generates previous values correctly. 
C) predicting the future values and wait for a pre-defined time period to examine how accurate the predictions were. 
D) adjusting the scale of the data.

Question 12

Causal models

Accepted Answer

A) provide evidence of a causal relationship between an independent variable and the variable to be forecast. 
B) use the average of the most recent data values in the time series as the forecast for the next period. 
C) occur whenever all the independent variables are previous values of the same time series. 
D) relate a time series to other variables that are believed to explain or cause its behavior. 
A) provide evidence of a causal relationship between an independent variable and the variable to be forecast. 
B) use the average of the most recent data values in the time series as the forecast for the next period. 
C) occur whenever all the independent variables are previous values of the same time series. 
D) relate a time series to other variables that are believed to explain or cause its behavior.

Question 13

Which of the following measures of forecast accuracy is susceptible to the problem of positive and negative forecast errors offsetting one another?

Accepted Answer

A) Mean absolute error 
B) Mean forecast error 
C) Mean squared error 
D) Mean absolute percentage error 
A) Mean absolute error 
B) Mean forecast error 
C) Mean squared error 
D) Mean absolute percentage error

Question 14

Which of the following states the objective of time series analysis?

Accepted Answer

A) To predict the values of a time series based on one or more other variables 
B) To analyze the cause-and-effect relationship of a dependent variable with a time series and one or more other variables 
C) To use present variable values to study what should have been the ideal past values 
D) To uncover a pattern in a time series and then extrapolate the pattern into the future 
A) To predict the values of a time series based on one or more other variables 
B) To analyze the cause-and-effect relationship of a dependent variable with a time series and one or more other variables 
C) To use present variable values to study what should have been the ideal past values 
D) To uncover a pattern in a time series and then extrapolate the pattern into the future

Question 15

Using a large value for order k in the moving averages method is effective in

Accepted Answer

A) tracking changes in a time series more quickly. 
B) smoothing out random fluctuations. 
C) providing a forecast when only the most recent time series are relevant. 
D) eliminating the effect of seasonal variations in the time series. 
A) tracking changes in a time series more quickly. 
B) smoothing out random fluctuations. 
C) providing a forecast when only the most recent time series are relevant. 
D) eliminating the effect of seasonal variations in the time series.

Question 16

The exponential smoothing forecast for period t + 1 is a weighted average of the

Accepted Answer

A) forecast value in period t with weight α and the actual value for period t with weight 1 - α. 
B) actual value in period t + 1 with weight α and the forecast for period t with weight 1 - α. 
C) forecast value in period t - 1 with weight α and the forecast for period t with weight 1 - α. 
D) actual value in period t with weight α and the forecast for period t with weight 1 - α. 
A) forecast value in period t with weight α and the actual value for period t with weight 1 - α. 
B) actual value in period t + 1 with weight α and the forecast for period t with weight 1 - α. 
C) forecast value in period t - 1 with weight α and the forecast for period t with weight 1 - α. 
D) actual value in period t with weight α and the forecast for period t with weight 1 - α.

Question 17

A causal model provides evidence of __________ between an independent variable and the variable to be forecast.

Accepted Answer

A) a causal relationship 
B) an association 
C) no relationship 
D) a seasonal relationship 
A) a causal relationship 
B) an association 
C) no relationship 
D) a seasonal relationship

Question 18

With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the

Accepted Answer

A) moving average. 
B) regression coefficient. 
C) smoothing constant. 
D) mean forecast error. 
A) moving average. 
B) regression coefficient. 
C) smoothing constant. 
D) mean forecast error.

Question 19

The moving averages and exponential smoothing methods are appropriate for a time series exhibiting

Accepted Answer

A) a horizontal pattern. 
B) a cyclical pattern. 
C) trends. 
D) seasonal effects. 
A) a horizontal pattern. 
B) a cyclical pattern. 
C) trends. 
D) seasonal effects.

Question 20

A time series with a seasonal pattern can be modeled by treating the season as a

Accepted Answer

A) predictor variable. 
B) dependent variable. 
C) dummy variable. 
D) quantitative variable. 
A) predictor variable. 
B) dependent variable. 
C) dummy variable. 
D) quantitative variable.

Which of the following statements is the objective of the moving averages and exponential smoothing methods?

Which of the following is not true of a stationary time series?

The process of __________ might be used to determine the value of the smoothing constant that minimizes the mean squared error.

An exponential trend pattern occurs when

A time series plot of a period of time (quarterly) versus quarterly sales (in $1,000s) is shown below. Which of the following data patterns best describes the scenario shown?

A time series that shows a recurring pattern over one year or less is said to follow a

In the moving averages method, the order k determines the

A positive forecast error indicates that the forecasting method ________ the dependent variable.

The moving averages method refers to a forecasting method that

A time series plot of a period of time (in weeks) versus sales (in 1,000's of gallons) is shown below. Which of the following data patterns best describes the scenario shown?

The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by

Causal models

Which of the following measures of forecast accuracy is susceptible to the problem of positive and negative forecast errors offsetting one another?

Which of the following states the objective of time series analysis?

Using a large value for order k in the moving averages method is effective in

The exponential smoothing forecast for period t + 1 is a weighted average of the

A causal model provides evidence of __________ between an independent variable and the variable to be forecast.

With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the

The moving averages and exponential smoothing methods are appropriate for a time series exhibiting

A time series with a seasonal pattern can be modeled by treating the season as a

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Predictive Data Mining

Spreadsheet Models

Monte Carlo Simulation

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters

Exam 8: Time Series Analysis and Forecasting

Which of the following statements is the objective of the moving averages and exponential smoothing methods?

Which of the following is not true of a stationary time series?

The process of __________ might be used to determine the value of the smoothing constant that minimizes the mean squared error.

An exponential trend pattern occurs when

A time series plot of a period of time (quarterly) versus quarterly sales (in $1,000s) is shown below. Which of the following data patterns best describes the scenario shown?

A time series that shows a recurring pattern over one year or less is said to follow a

In the moving averages method, the order k determines the

A positive forecast error indicates that the forecasting method ________ the dependent variable.

The moving averages method refers to a forecasting method that

A time series plot of a period of time (in weeks) versus sales (in 1,000's of gallons) is shown below. Which of the following data patterns best describes the scenario shown?

The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by

Causal models

Which of the following measures of forecast accuracy is susceptible to the problem of positive and negative forecast errors offsetting one another?

Which of the following states the objective of time series analysis?

Using a large value for order k in the moving averages method is effective in

The exponential smoothing forecast for period t + 1 is a weighted average of the

A causal model provides evidence of __________ between an independent variable and the variable to be forecast.

With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the

The moving averages and exponential smoothing methods are appropriate for a time series exhibiting

A time series with a seasonal pattern can be modeled by treating the season as a

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Predictive Data Mining

Spreadsheet Models

Monte Carlo Simulation

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters