Question 1

Which of the following data patterns best describes the scenario shown in the given time series plot?

Accepted Answer

A)  Linear trend pattern 
B)  Nonlinear trend pattern 
C)  Seasonal pattern 
D)  Cyclical pattern 
A)  Linear trend pattern 
B)  Nonlinear trend pattern 
C)  Seasonal pattern 
D)  Cyclical pattern

Question 2

Forecast error:

Accepted Answer

A)  takes a positive value when the forecast is too high. 
B)  cannot be negative. 
C)  cannot take a value of zero. 
D)  is associated with measuring forecast accuracy. 
A)  takes a positive value when the forecast is too high. 
B)  cannot be negative. 
C)  cannot take a value of zero. 
D)  is associated with measuring forecast accuracy.

Question 3

A _____ pattern exists when the data fluctuate randomly around a constant mean over time.

Accepted Answer

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

Question 4

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

Accepted Answer

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

Question 5

_____ uses a weighted average of past time series values as the forecast.

Accepted Answer

A)  The qualitative method 
B)  Exponential smoothing 
C)  Correlation analysis 
D)  The causal model 
A)  The qualitative method 
B)  Exponential smoothing 
C)  Correlation analysis 
D)  The causal model

Question 6

If the forecasted value of the time series variable for period 2 is 22.5 and the actual value observed for period 2 is 25, what is the forecast error in period 2?

Accepted Answer

A)  3 
B)  2 
C)  2.5 
D)  -2.5 
A)  3 
B)  2 
C)  2.5 
D)  -2.5

Question 7

The monthly market shares of General Electric Company for 12 consecutive months follow.
21.51, 22.43, 23.02, 23.03, 22.1, 23.37, 23.21, 24.6, 23.31, 23.94, 26.05, 26.65 a. Construct a time series plot. What type of pattern exists in the data?
b. Develop three-month and four-month moving averages for this time series. Does the three-month or the four-month moving average provide the better forecasts based on MSE? Explain.
c. What is the moving average forecast for the next month?

Accepted Answer

a.
 @#IMG-DLM& 
The data appear to follow a horizo

Question 8

The process of _____ might be used to determine the value of 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 9

_____ is the term used for a time series whose statistical properties are independent of time.

Accepted Answer

A)  Cluster 
B)  Stationary time series 
C)  Trend 
D)  Constant time series 
A)  Cluster 
B)  Stationary time series 
C)  Trend 
D)  Constant time series

Question 10

Consider the following time series data:
   
Using the average of all the historical data as a forecast for the next year, compute the following measures of forecast accuracy:a. Mean absolute error
b. Mean squared error
c. Mean absolute percentage error
d. What is the forecast for year 11?

Accepted Answer

The following table shows the calculatio

Question 11

Which of the following data patterns best describes the scenario shown in the given time series plot?

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 12

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 13

The moving averages method refers to a forecasting method that:

Accepted Answer

A)  moves up the average of every subsequent forecast by one. 
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 perio
D)  
A)  moves up the average of every subsequent forecast by one. 
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 perio
D)

Question 14

Consider the following time series data:
   a. Construct a time series plot. What type of pattern exists in the data?
b. Develop a three-year moving average for this time series. Compute MSE and a forecast for the year 11.

Accepted Answer

a.
 @#IMG-DLM& 
The time series data app

Question 15

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

Accepted Answer

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

Question 16

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 17

The value of an independent variable from the prior period is referred to as a _____.

Accepted Answer

A)  lagged variable 
B)  dummy variable 
C)  predictor variable 
D)  categorical variable 
A)  lagged variable 
B)  dummy variable 
C)  predictor variable 
D)  categorical variable

Question 18

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

Which of the following data patterns best describes the scenario shown in the given time series plot?

Forecast error:

A _____ pattern exists when the data fluctuate randomly around a constant mean over time.

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

_____ uses a weighted average of past time series values as the forecast.

If the forecasted value of the time series variable for period 2 is 22.5 and the actual value observed for period 2 is 25, what is the forecast error in period 2?

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

_____ is the term used for a time series whose statistical properties are independent of time.

Consider the following time series data: Using the average of all the historical data as a forecast for the next year, compute the following measures of forecast accuracy:a. Mean absolute error b. Mean squared error c. Mean absolute percentage error d. What is the forecast for year 11?

Which of the following data patterns best describes the scenario shown in the given time series plot?

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

The moving averages method refers to a forecasting method that:

Consider the following time series data: a. Construct a time series plot. What type of pattern exists in the data? b. Develop a three-year moving average for this time series. Compute MSE and a forecast for the year 11.

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

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 value of an independent variable from the prior period is referred to as a _____.

In the moving averages method, the order k determines the:

Introduction

Descriptive Statistics

Data Visualization

Linear Regression

Data Mining

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Monte Carlo Simulation

Decision Analysis

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Exam 5: Time Series Analysis and Forecasting

Which of the following data patterns best describes the scenario shown in the given time series plot?

Forecast error:

A _____ pattern exists when the data fluctuate randomly around a constant mean over time.

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

_____ uses a weighted average of past time series values as the forecast.

If the forecasted value of the time series variable for period 2 is 22.5 and the actual value observed for period 2 is 25, what is the forecast error in period 2?

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

_____ is the term used for a time series whose statistical properties are independent of time.

Consider the following time series data: Using the average of all the historical data as a forecast for the next year, compute the following measures of forecast accuracy:a. Mean absolute error b. Mean squared error c. Mean absolute percentage error d. What is the forecast for year 11?

Which of the following data patterns best describes the scenario shown in the given time series plot?

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

The moving averages method refers to a forecasting method that:

Consider the following time series data: a. Construct a time series plot. What type of pattern exists in the data? b. Develop a three-year moving average for this time series. Compute MSE and a forecast for the year 11.

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

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 value of an independent variable from the prior period is referred to as a _____.

In the moving averages method, the order k determines the:

Introduction

Descriptive Statistics

Data Visualization

Linear Regression

Data Mining

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Monte Carlo Simulation

Decision Analysis

Filters