Question 1

Seasonality in a time series is indicated by

Accepted Answer

A)  regular, repeating patterns in the data around a trend line. 
B)  regular patterns in the data around a trend line. 
C)  irregular patterns in the data around a trend line. 
D)  random patterns in the data around a trend line. 
A)  regular, repeating patterns in the data around a trend line. 
B)  regular patterns in the data around a trend line. 
C)  irregular patterns in the data around a trend line. 
D)  random patterns in the data around a trend line.

Question 2

A time series which has no significant upward or downward trend is referred to as

Accepted Answer

A)  static. 
B)  non-moving. 
C)  stationary. 
D)  non-stationary. 
A)  static. 
B)  non-moving. 
C)  stationary. 
D)  non-stationary.

Question 3

Exhibit 11.11
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using seasonal indices. The store has collected 12 quarters of data and needs your help to analyze the data. The relevant regression output is in the following table.
 $$\begin{array}{l}
\text { Ragression  Statistics }\ 
\begin{array} { | l | r | } 
\hline & \text { Coefficients } \
\hline \text { Intercept } & 263.4545 \
\hline \text { X Variable 1 } & 5.985514 \
\hline \text { X Variable 2 } & 4.922577 \
\hline
\end{array} 
\end{array}$$  
-Refer to Exhibit 11.11. What formula should be entered in cell F3 to compute the quadratic trend for year 1 Quarter 1?

Accepted Answer

A)  = 263.4545 * C3 + 5.985514 * D3 + 4.922577 
B)  = 263.4545 + 5.985514 * D3 + 4.922577 * C3 
C)  = 263.4545 + 5.985514 * C2 + 4.922577 * D2 
D)  = 263.4545 + 5.985514 * C3 + 4.922577 * D3 
A)  = 263.4545 * C3 + 5.985514 * D3 + 4.922577 
B)  = 263.4545 + 5.985514 * D3 + 4.922577 * C3 
C)  = 263.4545 + 5.985514 * C2 + 4.922577 * D2 
D)  = 263.4545 + 5.985514 * C3 + 4.922577 * D3

Question 4

Exhibit 11.18
The following questions use the data below.
A store wants to predict quarterly sales. The owner has collected 3 years of sales data and wants your help in analyzing the data using the multiplicative seasonal method.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|c|c|}
\hline & \mathrm{A} & \mathrm{B} & \mathrm{C} & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{G} & \mathrm{H} & \mathrm{I} & \mathrm{J} \
\hline 1 & & & \text { Time } & \text { Actual } & & \text { Seasonal } & & & & \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Factor } & \text { Forecast } & & & \
\hline 3 & 1 & 1 & 1 & 368 & 462.50 & 0.796 & & & \text { alpha } & 0.332167 \
\hline 4 & & 2 & 2 & 168 & 462.50 & 0.363 & & & \text { beta } & 1 \
\hline 5 & & 3 & 3 & 530 & 462.50 & 1.146 & & & & \
\hline 6 & & 4 & 4 & 784 & 462.50 & 1.695 & & & & \
\hline 7 & 2 & 1 & 5 & 770 & 630.32 & 1.222 & 368.00 & & & \
\hline 8 & & 2 & 6 & 354 & 744.66 & 0.475 & 228.96 & & & \
\hline 9 & & 3 & 7 & 1012 & 790.65 & 1.280 & 853.34 & & & \
\hline 10 & & 4 & 8 & 1244 & 771.79 & 1.612 & 1340.26 & & & \
\hline 11 & 3 & 1 & 9 & 1326 & 875.98 & 1.514 & 942.82 & & & \
\hline 12 & & 2 & 10 & 986 & 1273.96 & 0.774 & 416.43 & & & \
\hline 13 & & 3 & 11 & 1624 & 1272.25 & 1.276 & 1630.62 & & & \
\hline 14 & & 4 & 12 & 2090 & 1280.35 & 1.632 & 2050.66 & & & \
\hline 15 & & & & & & & & & & \
\hline 16 & & & & & & & 85564.040 & & & \
\hline
\end{array}\)

-Refer to Exhibit 11.18. What is the forecast for time period 13?

Accepted Answer

The answer of Exhibit 11.18
The following questions use the data...

Question 5

Exhibit 11.3
The following questions use the data below.
Honest Al's Used Cars wants to predict how many cars are sold each month. He has collected data for 12 months. He needs your help in analyzing this data using exponential smoothing.
 $\begin{array}{|c|c|c|c|c|c|c|} 
\hline& \text { A } & \text { B } & \text { C } & \text { D } & \text { E } & \text { F } \
\hline 1 & & \text { Number of } & \text { Exp Smoothing } & & & \
\hline 2 & \text { Time Period } & \text { Cars Sold } & \text { Prediction } & & & \
\hline 3 & 1 & 70 & 70.00 & & \text { alpha } & 0.346 \
\hline 4 & 2 & 80 & 70.00 & & & \
\hline 5 & 3 & 66 & 73.46 & & & \
\hline 6 & 4 & 74 & 70.88 & & & \
\hline 7 & 5 & 64 & 71.96 & & & \
\hline 8 & 6 & 76 & 69.20 & & & \
\hline 9 & 7 & 72 & 71.56 & & & \
\hline 10 & 8 & 82 & 71.71 & & & \
\hline 11 & 9 & 82 & 75.27 & & & \
\hline 12 & 10 & 76 & 77.60 & & & \
\hline 13 & 11 & 84 & 77.05 & & & \
\hline 14 & 12 & 80 & 79.45 & & & \
\hline 15 & & & & & & \
\hline 16 & & \mathrm{MSE} & 39.79 & & & \
\hline
\end{array}$

-Refer to Exhibit 11.3. Assume the forecasted value for month 13 is 79.64. What is the forecasted value for month 16?

Accepted Answer

A)  85.54. 
B)  83.64. 
C)  79.64. 
D)  82.00. 
A)  85.54. 
B)  83.64. 
C)  79.64. 
D)  82.00.

Question 6

As alpha increases the exponential smoothing model

Accepted Answer

A)  produces sluggish forecasts. 
B)  reacts quickly to changes in the data. 
C)  reacts slowly to changes in the data. 
D)  does not change. 
A)  produces sluggish forecasts. 
B)  reacts quickly to changes in the data. 
C)  reacts slowly to changes in the data. 
D)  does not change.

Question 7

Exhibit 11.20
The following questions use the data below.
A store wants to predict quarterly sales. The owner has collected 3 years of sales data and wants your help in analyzing the data using Holt's method.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|c|c|} 
\hline& \text { A } & \text { B } & \text { C } & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{G} & \mathrm{H} & \mathrm{I} & \mathrm{J} \
\hline 1 & & & \text { Time } & \text { Actual } & \text { Base } & & \text { Predicted } & & & \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Trend } & \text { Sales } & & \
\hline 3 & 1 & 1 & 1 & 368 & 368.0 & 0.0 & & & \text { alpha } & 0.4 \
\hline 4 & & 2 & 2 & 168 & 288.0 & -48.0 & 368.0 & & \text { beta } & 0.6 \
\hline 5 & & 3 & 3 & 530 & 356.0 & 21.6 & 240.0 & & \
\hline 6 & & 4 & 4 & 784 & 540.2 & 119.1 & 377.6 & & & \
\hline 7 & 2 & 1 & 5 & 770 & 703.6 & 145.7 & 659.3 & & & \
\hline 8 & & 2 & 6 & 354 & 651.2 & 26.8 & 849.3 & & & \
\hline 9 & & 3 & 7 & 1012 & 811.6 & 107.0 & 678.0 & & & \
\hline 10 & & 4 & 8 & 1244 & 1048.8 & 185.1 & 918.6 & & & \
\hline 11 & 3 & 1 & 9 & 1326 & 1270.7 & 207.2 & 1233.9 & & & \
\hline 12 & & 2 & 10 & 986 & 1281.2 & 89.1 & 1477.9 & & & \
\hline 13 & & 3 & 11 & 1624 & 1471.8 & 150.0 & 1370.3 & & & \
\hline 14 & & 4 & 12 & 2090 & 1809.1 & 262.4 & 1621.8 & & & \
\hline 15 & & & & & & & & & & \
\hline 16 & & & & & &  \text { MSE } & 30469.5 & &\
\hline
\end{array}\)

-Refer to Exhibit 11.20. What is the forecast for time period 13?

Accepted Answer

The answer of Exhibit 11.20
The following questions use the data...

Question 8

Which of the following is the common approach to time-series analysis?

Accepted Answer

A)  Try several techniques and use the best results. 
B)  Plot the data and count the peaks to determine a value for k. 
C)  Plot the data and use the TREND() function. 
D)  Use a stationary model since it is the most robust. 
A)  Try several techniques and use the best results. 
B)  Plot the data and count the peaks to determine a value for k. 
C)  Plot the data and use the TREND() function. 
D)  Use a stationary model since it is the most robust.

Question 9

Exhibit 11.11
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using seasonal indices. The store has collected 12 quarters of data and needs your help to analyze the data. The relevant regression output is in the following table.
 $$\begin{array}{l}
\text { Ragression  Statistics }\ 
\begin{array} { | l | r | } 
\hline & \text { Coefficients } \
\hline \text { Intercept } & 263.4545 \
\hline \text { X Variable 1 } & 5.985514 \
\hline \text { X Variable 2 } & 4.922577 \
\hline
\end{array} 
\end{array}$$  
-Refer to Exhibit 11.11. What formula should be entered in cell G3 to compute the "Actual as a % of Trend" value for year 1 Quarter 1?

Accepted Answer

A)  =E3/H3 
B)  =F3/H3 
C)  =F3/E3 
D)  =E3/F3 
A)  =E3/H3 
B)  =F3/H3 
C)  =F3/E3 
D)  =E3/F3

Question 10

Exhibit 11.10
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using a quadratic trend model. The store has collected 12 quarters of data and needs your help to analyze the data. The relevant regression output is in the following table.
 $$\begin{array}{l}
\text { Regression Statistics  }\ 
\begin{array} { | l | r | } 
\hline & \text { Cafficienfs } \
\hline \text { Intercagt } & 263.4545 \
\hline \mathrm { X } \text { Varable 1 } & 5.985514 \
\hline \mathrm { X } \text { Variable 2 } & 4.922577 \
\hline
\end{array}
\end{array}$$ $\begin{array}{|c|c|c|c|c|c|c|}
\hline & \text { A } & \text { B } & \text { C } & \mathrm{D} & \mathrm{E} & \mathrm{F} \
\hline 1 & & & \text { Time } & & \text { Actual } & \text { Quadratic } \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Time } 2 & \text { Sales } & \text { Trend } \
\hline 3 & 1 & 1 & 1 & 1 & 284 & \
\hline 4 & & 2 & 2 & 4 & 184 & 295.1 \
\hline 5 & & 3 & 3 & 9 & 365 & 325.7 \
\hline 6 & & 4 & 4 & 16 & 492 & 366.2 \
\hline 7 & 2 & 1 & 5 & 25 & 485 & 416.4 \
\hline 8 & & 2 & 6 & 36 & 277 & 476.6 \
\hline 9 & & 3 & 7 & 49 & 606 & 546.6 \
\hline 10 & & 4 & 8 & 64 & 722 & 626.4 \
\hline 11 & 3 & 1 & 9 & 81 & 763 & 716.1 \
\hline 12 & & 2 & 10 & 100 & 593 & 815.6 \
\hline 13 & & 3 & 11 & 121 & 912 & 924.9 \
\hline 14 & & 4 & 12 & 144 & 1145 & 1044.1 \
\hline
\end{array}$

-Refer to Exhibit 11.10. How is a quadratic term added to the problem if we want to develop a quadratic trend model?

Accepted Answer

A)  Add a column containing Time2. 
B)  Add a column containing Actual Sales2. 
C)  Increase the Input X Range in the Regression command settings dialog box. 
D)  Square the coefficient for Time in the regression model. 
A)  Add a column containing Time2. 
B)  Add a column containing Actual Sales2. 
C)  Increase the Input X Range in the Regression command settings dialog box. 
D)  Square the coefficient for Time in the regression model.

Question 11

Exhibit 11.12
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using a seasonal regression model. The store has collected 12 quarters of data and needs your help to analyze the data. The relevant regression output is provided in the following table.
 $\begin{array}{|l|r|}
\hline{\text { Regression Statistics }} \
\hline & \text { Coefficients } \
\hline \text { Intercept } & 388.88 \
\hline \text { X Variable 1 } & 10.052 \
\hline \text { X Variable 2 } & 4.248 \
\hline \text { X Variable 3 } & -79.917 \
\hline \text { X Variable 4 } & -296.008 \
\hline \text { X Variable 5 } & -84.924 \
\hline
\end{array}$
  
-Refer to Exhibit 11.12. What Excel command can be used in cells F4:F14 in lieu of a formula based on the regression statistics?

Accepted Answer

A)  =TREND($H$3:$H$14,$C$3:$G$14, C3:G3) 
B)  =TREND($H$3:$H$14,$B$3:$G$14, B3:G3) 
C)  =TREND($H$3:$H$14,$A$3:$G$14, A3:G3) 
D)  =TREND($H$3:$H$14,$C$3:$D$14, C3:D3) 
A)  =TREND($H$3:$H$14,$C$3:$G$14, C3:G3) 
B)  =TREND($H$3:$H$14,$B$3:$G$14, B3:G3) 
C)  =TREND($H$3:$H$14,$A$3:$G$14, A3:G3) 
D)  =TREND($H$3:$H$14,$C$3:$D$14, C3:D3)

Seasonality in a time series is indicated by

A time series which has no significant upward or downward trend is referred to as

As alpha increases the exponential smoothing model

Which of the following is the common approach to time-series analysis?

Introduction to Modeling and Decision Analysis

Introduction to Optimization and Linear Programming

Modeling and Solving Lp Problems in a Spreadsheet

Sensitivity Analysis and the Simplex Method

Network Modeling

Integer Linear Programming

Goal Programming and Multiple Objective Optimization

Nonlinear Programming and Evolutionary Optimization

Regression Analysis

Discriminant Analysis

Introduction to Simulation Using Risk Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

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Exam 11: Time Series Forecasting

Seasonality in a time series is indicated by

A time series which has no significant upward or downward trend is referred to as

As alpha increases the exponential smoothing model

Which of the following is the common approach to time-series analysis?

Introduction to Modeling and Decision Analysis

Introduction to Optimization and Linear Programming

Modeling and Solving Lp Problems in a Spreadsheet

Sensitivity Analysis and the Simplex Method

Network Modeling

Integer Linear Programming

Goal Programming and Multiple Objective Optimization

Nonlinear Programming and Evolutionary Optimization

Regression Analysis

Discriminant Analysis

Introduction to Simulation Using Risk Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

Filters