Question 1

A seasonal index must be between -1 and +1.

Accepted Answer

A) True 
 B)False

Question 2

Consider the actual and forecast values contained in the table.   What is the MAD of the forecast?

Accepted Answer

A) 0.60 
B) 0.65 
C) 0.70 
D) 0.75 
A) 0.60 
B) 0.65 
C) 0.70 
D) 0.75

Question 3

The following table shows the number of pies consumed by the deans' suite during a monthly pie-eating contest.   What is the forecast tracking signal for June?

Accepted Answer

A) -0.75 
B) -2.67 
C) 0.75 
D) 2.67 
A) -0.75 
B) -2.67 
C) 0.75 
D) 2.67

Question 4

In general terms, describe what qualitative forecasting models are.

Accepted Answer

Qualitative forecasting models

Question 5

Which of the following is a technique used to determine forecasting accuracy?

Accepted Answer

A) exponential smoothing 
B) regression 
C) Delphi method 
D) mean absolute percent error 
A) exponential smoothing 
B) regression 
C) Delphi method 
D) mean absolute percent error

Question 6

Which of the following methods tells whether the forecast tends to be too high or too low?

Accepted Answer

A) MAD 
B) MSE 
C) MAPE 
D) bias 
A) MAD 
B) MSE 
C) MAPE 
D) bias

Question 7

Consider the actual and forecast values contained in the table.   What is the MAPE of the forecast?

Accepted Answer

A) 2.92% 
B) 3.08% 
C) 3.17% 
D) 3.26% 
A) 2.92% 
B) 3.08% 
C) 3.17% 
D) 3.26%

Question 8

Daily high temperatures in the city of Houston for the last week have been: 93, 94, 93, 95, 92, 86, 98 (yesterday).
(a)Forecast the high temperature today using a three-day moving average.
(b)Forecast the high temperature today using a two-day moving average.
(c)Calculate the mean absolute deviation based on a two-day moving average, covering all days in which you can have a forecast and an actual temperature.

Accepted Answer

(a)(92 + 86 + 98)/3 = 92 (b)(8

Question 9

The process of isolating linear trend and seasonal factors to develop more accurate forecasts is called

Accepted Answer

A) regression. 
B) decomposition. 
C) smoothing. 
D) monitoring. 
A) regression. 
B) decomposition. 
C) smoothing. 
D) monitoring.

Question 10

State the mathematical expression for exponential smoothing.

Accepted Answer

Ft + 1 = F

Question 11

Which of the following methods produces a particularly stiff penalty in periods with large forecast errors?

Accepted Answer

A) MAD 
B) MSE 
C) MAPE 
D) decomposition 
A) MAD 
B) MSE 
C) MAPE 
D) decomposition

Question 12

A scatter diagram for a time series may be plotted on a two-dimensional graph with the horizontal axis representing the variable to be forecast (such as sales).

Accepted Answer

A) True 
 B)False

Question 13

Which of the following is not a characteristic of trend projections?

Accepted Answer

A) The variable being predicted is the Y variable. 
B) Time is the X variable. 
C) It is useful for predicting the value of one variable based on time trend. 
D) A negative intercept term always implies that the dependent variable is decreasing over time. 
A) The variable being predicted is the Y variable. 
B) Time is the X variable. 
C) It is useful for predicting the value of one variable based on time trend. 
D) A negative intercept term always implies that the dependent variable is decreasing over time.

Question 14

List four components of TIME SERIES data.

Accepted Answer

trend, sea

Question 15

What is one advantage of using causal models over time series or qualitative models?

Accepted Answer

Use of the causal model requires that th

Question 16

Briefly describe the structure of a scatter diagram for a time series.

Accepted Answer

A scatter diagram for a time series may

Question 17

List the steps to develop a forecast using the decomposition method.

Accepted Answer

1.Compute seasonal indices using CMAs. 2

Question 18

Which of the following statements about the decomposition method is false?

Accepted Answer

A) The process of "deseasonalizing" involves multiplying by a seasonal index. 
B) Dummy variables are used in a regression model as part of an additive approach to seasonality. 
C) Computing seasonal indices is the first step of the decomposition method. 
D) Data is "deseasonalized" after the trend line is found. 
A) The process of "deseasonalizing" involves multiplying by a seasonal index. 
B) Dummy variables are used in a regression model as part of an additive approach to seasonality. 
C) Computing seasonal indices is the first step of the decomposition method. 
D) Data is "deseasonalized" after the trend line is found.

Question 19

A time series exhibiting only random variations is best fit by a horizontal line.

Accepted Answer

A) True 
 B)False

Question 20

The tracking signal is the running sum of the forecast errors divided by the

Accepted Answer

A) MAD. 
B) MSE. 
C) RSFE. 
D) bias. 
A) MAD. 
B) MSE. 
C) RSFE. 
D) bias.

Exam 5: Forecasting

A seasonal index must be between -1 and +1.

Consider the actual and forecast values contained in the table. What is the MAD of the forecast?

The following table shows the number of pies consumed by the deans' suite during a monthly pie-eating contest. What is the forecast tracking signal for June?

In general terms, describe what qualitative forecasting models are.

Which of the following is a technique used to determine forecasting accuracy?

Which of the following methods tells whether the forecast tends to be too high or too low?

Consider the actual and forecast values contained in the table. What is the MAPE of the forecast?

The process of isolating linear trend and seasonal factors to develop more accurate forecasts is called

State the mathematical expression for exponential smoothing.

Which of the following methods produces a particularly stiff penalty in periods with large forecast errors?

A scatter diagram for a time series may be plotted on a two-dimensional graph with the horizontal axis representing the variable to be forecast (such as sales).

Which of the following is not a characteristic of trend projections?

List four components of TIME SERIES data.

What is one advantage of using causal models over time series or qualitative models?

Briefly describe the structure of a scatter diagram for a time series.

List the steps to develop a forecast using the decomposition method.

Which of the following statements about the decomposition method is false?

A time series exhibiting only random variations is best fit by a horizontal line.

The tracking signal is the running sum of the forecast errors divided by the

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