Question 1

Why might we not be able to build a regression model to predict a dependent variable?

Accepted Answer

A)  We might not know the independent variables. 
B)  There might not be any data available for the independent variables. 
C)  The regression model might not fit the data well. 
D)  All of these are true. 
A)  We might not know the independent variables. 
B)  There might not be any data available for the independent variables. 
C)  The regression model might not fit the data well. 
D)  All of these are true.

Question 2

Which of the following is not a quantitative technique for evaluating the accuracy of a time-series modeling technique?

Accepted Answer

A)  Constructing line graphs of the data. 
B)  The mean absolute deviation. 
C)  The mean absolute percent error. 
D)  The root mean square error. 
A)  Constructing line graphs of the data. 
B)  The mean absolute deviation. 
C)  The mean absolute percent error. 
D)  The root mean square error.

Question 3

Exhibit 11.22
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. He wants to use regression and a linear trend model.
 $\begin{array}{|l|r|}
\hline {\text { Regression Statistics }} \
\hline \text { Multiple R } & 0.895 \
\hline \text { R Square } & 0.791 \
\hline \text { Adjusted R Square } & 0.773 \
\hline \text { Standard Error } & 269.406 \
\hline \text { Observations } & 12 \
\hline & \text { Coefficients } \
\hline \text { Intercept } & 28.273 \
\hline \text { X Variable 1 } & 139.958 \
\hline
\end{array}$
 $\begin{array}{|c|c|c|c|c|c|}
\hline & \text { A } & \text { B } & \text { C } & \text { D } & \text { E } \
\hline 1 & & & \text { Time } & \text { Actual } & \text { Linear } \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Trend } \
\hline 3 & 1 & 1 & 1 & 368 & 168.2 \
\hline 4 & & 2 & 2 & 168 & 308.2 \
\hline 5 & & 3 & 3 & 530 & 448.1 \
\hline 6 & & 4 & 4 & 784 & 588.1 \
\hline 7 & 2 & 1 & 5 & 770 & 728.1 \
\hline 8 & & 2 & 6 & 354 & 868.0 \
\hline 9 & & 3 & 7 & 1012 & 1008.0 \
\hline 10 & & 4 & 8 & 1244 & 1147.9 \
\hline 11 & 3 & 1 & 9 & 1326 & 1287.9 \
\hline 12 & & 2 & 10 & 986 & 1427.9 \
\hline 13 & & 3 & 11 & 1624 & 1567.8 \
\hline 14 & & 4 & 12 & 2090 & 1707.8\
\hline 
\end{array}$

-Refer to Exhibit 11.22. What is the forecast for time period 13?

Accepted Answer

The answer of Exhibit 11.22
The following questions use the data...

Question 4

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. What Excel command can be used in cells F4:F14 in lieu of a formula based on the regression statistics?

Accepted Answer

A)  =TREND($E$3:$E$14,$C$3:$C$14,C4) 
B)  =TREND($E$3:$E$14,$C$3:$D$14,C4:D4) 
C)  =TREND($E$3:$E$14,$C$3:$D$14,D4) 
D)  =TREND($E$3:$E$14,$B$3:$D$14,B4:D4) 
A)  =TREND($E$3:$E$14,$C$3:$C$14,C4) 
B)  =TREND($E$3:$E$14,$C$3:$D$14,C4:D4) 
C)  =TREND($E$3:$E$14,$C$3:$D$14,D4) 
D)  =TREND($E$3:$E$14,$B$3:$D$14,B4:D4)

Question 5

Exhibit 11.16
The following questions use the data below.
The owner of Tim's Toys wants to predict monthly sales. He has collected data for 12 months. He needs your help in analyzing this data using exponential smoothing.
 $\begin{array}{|c|c|c|c|c|c|c|} 
\hline & \text { A } & \text { B } & \text { C } & \text { D } & \text { E } & \text { F } \
\hline 1 & & \text { Number of } & \text { Exp Smoothing } & & & \
\hline 2 & \text { Time Period } & \text { Toys Sold } & \text { Prediction } & & & \
\hline 3 & 1 & 174 & 174.00 & & \text { alpha } & 0.440 \
\hline 4 & 2 & 189 & 174.00 & & & \
\hline 5 & 3 & 168 & 180.60 & & & \
\hline 6 & 4 & 180 & 175.06 & & & \
\hline 7 & 5 & 165 & 177.23 & & & \
\hline 8 & 6 & 183 & 171.85 & & & \
\hline 9 & 7 & 177 & 176.76 & & & \
\hline 10 & 8 & 192 & 176.86 & & & \
\hline 11 & 9 & 192 & 183.52 & & & \
\hline 12 & 10 & 183 & 187.25 & & & \
\hline 13 & 11 & 195 & 185.38 & & & \
\hline 14 & 12 & 189 & 189.61 & & & \
\hline 15 & & & & & & \
\hline 16 & & \text { MSE } & 91.18 & & & \
\hline
\end{array}$

-Refer to Exhibit 11.16. What is the forecast for time period 13?

Accepted Answer

The answer of Exhibit 11.16
The following questions use the data...

Question 6

Exhibit 11.4
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using the additive seasonal method. The store has collected 12 quarters of data and needs your help to analyze the data.
  
-Refer to Exhibit 11.4. What formula should be entered in cell F7 to compute the seasonal factor using the additive seasonal effects model?

Accepted Answer

A)  =$J$3*D4+(1-$J$3)*(E3+F3) 
B)  =$J$4*(D7-E7)+(1-$J$4)*F3 
C)  =$J$4*(E7-E6)+(1-$J$4)*E6 
D)  =$J$3*G3+(1-$J$3)*(D3+G3) 
A)  =$J$3*D4+(1-$J$3)*(E3+F3) 
B)  =$J$4*(D7-E7)+(1-$J$4)*F3 
C)  =$J$4*(E7-E6)+(1-$J$4)*E6 
D)  =$J$3*G3+(1-$J$3)*(D3+G3)

Question 7

Exhibit 11.4
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using the additive seasonal method. The store has collected 12 quarters of data and needs your help to analyze the data.
  
-Refer to Exhibit 11.4. What formula should be entered in cell E7 to compute the remaining expected levels?

Accepted Answer

A)  =$J$3*(D7-D3) + (1-$J$3)*E6 
B)  =$J$3*(D7-D6) + (1-$J$3)*E6 
C)  =$J$4*(D7-D3) + (1-$J$4)*E6 
D)  =$J$4*(D7-D6) + (1-$J$4)*E6 
A)  =$J$3*(D7-D3) + (1-$J$3)*E6 
B)  =$J$3*(D7-D6) + (1-$J$3)*E6 
C)  =$J$4*(D7-D3) + (1-$J$4)*E6 
D)  =$J$4*(D7-D6) + (1-$J$4)*E6

Question 8

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 is the Input Y Range in the Regression command settings dialog box?

Accepted Answer

A)  $C$3:$C$14 
B)  $H$3:$H$14 
C)  $C$3:$G$14 
D)  $H$3:$I$14 
A)  $C$3:$C$14 
B)  $H$3:$H$14 
C)  $C$3:$G$14 
D)  $H$3:$I$14

Question 9

Exhibit 11.17
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 additive seasonal method.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|c|c|}  
\hline& \text { A } & \text { B } & \text { C } & \text { D } & \text { E } & \text { F } & \text { G } & \text { H } & \text { I } & \mathrm{J} \
\hline 1 & & & \text { Time } & \text { Actual } & & \text { Seasonal } & & & & \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Factor } & \text { Forecast } & & & \
\hline 3 & 1991 & 1 & 1 & 368 & 462.50 & -94.500 & & & \text { alpha } & 0.764197 \
\hline 4 & & 2 & 2 & 168 & 462.50 & -294.500 & & & \text { beta } & 1 \
\hline 5 & & 3 & 3 & 530 & 462.50 & 67.500 & & & & \
\hline 6 & & 4 & 4 & 784 & 462.50 & 321.500 & & & & \
\hline 7 & 1992 & 1 & 5 & 770 & 769.71 & 0.293 & 368.00 & & & \
\hline 8 & & 2 & 6 & 354 & 677.08 & -323.081 & 475.21 & & & \
\hline 9 & & 3 & 7 & 1012 & 881.44 & 130.558 & 744.58 & & & \
\hline 10 & & 4 & 8 & 1244 & 912.82 & 331.182 & 1202.94 & & & \
\hline 11 & 1993 & 1 & 9 & 1326 & 1228.35 & 97.653 & 913.11 & & & \
\hline 12 & & 2 & 10 & 986 & 1290.04 & -304.044 & 905.27 & & & \
\hline 13 & & 3 & 11 & 1624 & 1445.48 & 178.520 & 1420.60 & & & \
\hline 14 & & 4 & 12 & 2090 & 1684.93 & 405.068 & 1776.66 & & & \
\hline 15 & & & & & & & & & & \
\hline 16 & & & & & &&70755.110 & & & \
\hline
\end{array}\)

-Refer to Exhibit 11.17. What is the forecast for time period 13?

Accepted Answer

The answer of Exhibit 11.17
The following questions use the data...

Question 10

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 formula should be entered in cell E3 to compute the value for the indicator variable for year 1 Quarter 1?

Accepted Answer

A)  =IF($B$3$E$2,1,0) 
B)  =IF($B3=E$2,1) 
C)  =IF($B$3=$E$2,0,1) 
D)  =IF($B3=E$2,1,0) 
A)  =IF($B$3$E$2,1,0) 
B)  =IF($B3=E$2,1) 
C)  =IF($B$3=$E$2,0,1) 
D)  =IF($B3=E$2,1,0)

Question 11

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. What is the exponential smoothing forecast for month 2?

Accepted Answer

A)  69.75 F1F1F1S1?F1F1F10 forecast < 70.25 
B)  73.00 F1F1F1S1?F1F1F10 forecast < 73.50 
C)  74.75 F1F1F1S1?F1F1F10 forecast < 75.25 
D)  79.75 F1F1F1S1?F1F1F10 forecast < 81.25 
A)  69.75 F1F1F1S1?F1F1F10 forecast < 70.25 
B)  73.00 F1F1F1S1?F1F1F10 forecast < 73.50 
C)  74.75 F1F1F1S1?F1F1F10 forecast < 75.25 
D)  79.75 F1F1F1S1?F1F1F10 forecast < 81.25

Question 12

Exhibit 11.2
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 weighted moving averages.
 $\begin{array}{|c|c|c|c|c|c|c|} 
\hline & \text { A } & \text { B } & \text { C } & \text { D } & \text { E } & \text { F } \
\hline 1 & & \text { Number of } & \text { 2-Month Weighted } & & & \
\hline 2 & \text { Time Period } & \text { Cars Sold } & \text { Moving Avg. } & & \text { Weights } & \
\hline 3 & 1 & 70 & & & \text { W1 } & 0.244 \
\hline 4 & 2 & 80 & & & \text { W2 } & 0.756 \
\hline 5 & 3 & 66 & & & \text { sum } & 1.000 \
\hline 6 & 4 & 74 & 76.59 & & & \
\hline 7 & 5 & 64 & 67.95 & & & \
\hline 8 & 6 & 76 & 71.56 & & & \
\hline 9 & 7 & 72 & 66.93 & & & \
\hline 10 & 8 & 82 & 75.02 & & & \
\hline 11 & 9 & 82 & 74.44 & & & \
\hline 12 & 10 & 76 & 82.00 & & & \
\hline 13 & 11 & 84 & 80.54 & & & \
\hline 14 & 12 & 80 & 77.95 & & & \
\hline 15 & & & & & & \
\hline 16 & & \text { MSE } & 26.72 & & & \
\hline
\end{array}$

-Refer to Exhibit 11.2. Which cell in the spreadsheet is the objective cell in the Risk Solver Platform (RSP) task pane area?

Accepted Answer

A)  F3 
B)  F4 
C)  F5 
D)  C16 
A)  F3 
B)  F4 
C)  F5 
D)  C16

Question 13

How many indicator variables are required if there are p seasons in a time series and you are forecasting with a seasonal regression model?

Accepted Answer

A)  p F1F1F1S1F1F1F10 1 
B)  p 
C)  p + 1 
D)  p + 2 
A)  p F1F1F1S1F1F1F10 1 
B)  p 
C)  p + 1 
D)  p + 2

Question 14

Exhibit 11.24
The following questions use the data below.
A store wants to predict quarterly sales. The owners have has collected 3 years of sales data and wants your help in analyzing the data. They want to use a quadratic trend model with seasonality to forecast sales.
 $\begin{array}{|l|r|}
\hline {\text { Regression Statistics }} \
\hline & \text { Coefficients } \
\hline \text { Intercept } & 56.29 \
\hline \text { X Variable 1 } & 3.59 \
\hline \text { X Variable 2 } & 0.08 \
\hline
\end{array}$
  
-Refer to Exhibit 11.24. What is the forecast for time period 13?

Accepted Answer

The answer of Exhibit 11.24
The following questions use the data...

Question 15

Exhibit 11.7
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using Holt's method. The store has collected 12 quarters of data and needs your help to analyze the data.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|c|c|} 
\hline& \text { A } & \text { B } & \mathrm{C} & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{G} & \mathrm{H} & \mathrm{I} & \mathrm{J} \
\hline 1 & & & \text { Time } & \text { Actual } & \text { Base } & & \text { Predicted } & & & \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Trend } & \text { Sales } & & & \
\hline 3 & 1 & 1 & 1 & 284 & & & & & \text { alpha } & 0.5 \
\hline 4 & & 2 & 2 & 184 & & & & & \text { beta } & 0.5 \
\hline 5 & & 3 & 3 & 365 & 287.0 & 14.0 & 209.0 & & \
\hline 6 & & 4 & 4 & 492 & 396.5 & 61.8 & 301.0 & & & \
\hline 7 & 2 & 1 & 5 & 485 & 471.6 & 68.4 & 458.3 & & & \
\hline 8 & & 2 & 6 & 277 & 408.5 & 2.7 & 540.1 & & & \
\hline 9 & & 3 & 7 & 606 & 508.6 & 51.4 & 411.2 & & & \
\hline 10 & & 4 & 8 & 722 & 641.0 & 91.9 & 560.0 & & & \
\hline 11 & 3 & 1 & 9 & 763 & 747.9 & 99.4 & 732.9 & & & \
\hline 12 & & 2 & 10 & 593 & 720.2 & 35.8 & 847.3 & & & \
\hline 13 & & 3 & 11 & 912 & 834.0 & 74.8 & 756.0 & & & \
\hline 14 & & 4 & 12 & 1145 & 1026.9 & 133.9 & 908.8 & & & \
\hline 15 & & & & & & & & & & \
\hline 16 & & & & & & &  31877.0 & &\
\hline 
\end{array}\)

-Refer to Exhibit 11.7. What formula should be entered in cell F4 to compute the trend when using Holt's method?

Accepted Answer

A)  =$J$3*D4+(1-$J$3)*(E3+F3) 
B)  =$J$4*(E4-E3)+(1-$J$4)*F3 
C)  =$J$4*(E4-E3)+(1-$J$4)*G3 
D)  =$J$4*G3+(1-$J$4)*(D3+G3) 
A)  =$J$3*D4+(1-$J$3)*(E3+F3) 
B)  =$J$4*(E4-E3)+(1-$J$4)*F3 
C)  =$J$4*(E4-E3)+(1-$J$4)*G3 
D)  =$J$4*G3+(1-$J$4)*(D3+G3)

Question 16

Exhibit 11.2
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 weighted moving averages.
 $\begin{array}{|c|c|c|c|c|c|c|} 
\hline & \text { A } & \text { B } & \text { C } & \text { D } & \text { E } & \text { F } \
\hline 1 & & \text { Number of } & \text { 2-Month Weighted } & & & \
\hline 2 & \text { Time Period } & \text { Cars Sold } & \text { Moving Avg. } & & \text { Weights } & \
\hline 3 & 1 & 70 & & & \text { W1 } & 0.244 \
\hline 4 & 2 & 80 & & & \text { W2 } & 0.756 \
\hline 5 & 3 & 66 & & & \text { sum } & 1.000 \
\hline 6 & 4 & 74 & 76.59 & & & \
\hline 7 & 5 & 64 & 67.95 & & & \
\hline 8 & 6 & 76 & 71.56 & & & \
\hline 9 & 7 & 72 & 66.93 & & & \
\hline 10 & 8 & 82 & 75.02 & & & \
\hline 11 & 9 & 82 & 74.44 & & & \
\hline 12 & 10 & 76 & 82.00 & & & \
\hline 13 & 11 & 84 & 80.54 & & & \
\hline 14 & 12 & 80 & 77.95 & & & \
\hline 15 & & & & & & \
\hline 16 & & \text { MSE } & 26.72 & & & \
\hline
\end{array}$

-Refer to Exhibit 11.2. What would be the forecasted value for time period 13?

Accepted Answer

A)  83.024. 
B)  80.796. 
C)  79.245. 
D)  79.908. 
A)  83.024. 
B)  80.796. 
C)  79.245. 
D)  79.908.

Question 17

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. What is the Input X Range in the Regression command settings dialog box?

Accepted Answer

A)  B3:B14 
B)  C3:C14 
C)  C3:D14 
D)  C3:E14 
A)  B3:B14 
B)  C3:C14 
C)  C3:D14 
D)  C3:E14

Question 18

Exhibit 11.5
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 effects model.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|c|c|} 
\hline& \text { A } & \mathrm{B} & \mathrm{C} & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{G} & \mathrm{H} & \mathrm{I} & \mathrm{J} \
\hline 1 & & & \text { Time } & \text { Actual } & & \text { Seasonal } & & & & \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Factor } & \text { Forecast } & & & \
\hline 3 & 1 & 1 & 1 & 368 & 462.50 & 0.796 & & & \text { alpha } & 0.332167 \
\hline 4 & & 2 & 2 & 168 & 462.50 & 0.363 & & & \text { beta } & 1 \
\hline 5 & & 3 & 3 & 530 & 462.50 & 1.146 & & & & \
\hline 6 & & 4 & 4 & 784 & 462.50 & 1.695 & & & & \
\hline 7 & 2 & 1 & 5 & 770 & 630.32 & 1.222 & 368.00 & & \
\hline 8 & & 2 & 6 & 354 & 744.66 & 0.475 & 228.96 & & & \
\hline 9 & & 3 & 7 & 1012 & 790.65 & 1.280 & 853.34 & & & \
\hline 10 & & 4 & 8 & 1244 & 771.79 & 1.612 & 1340.26 & & & \
\hline 11 & 3 & 1 & 9 & 1326 & 875.98 & 1.514 & 942.82 & & & \
\hline 12 & & 2 & 10 & 986 & 1273.96 & 0.774 & 416.43 & & & \
\hline 13 & & 3 & 11 & 1624 & 1272.25 & 1.276 & 1630.62 & & & \
\hline 14 & & 4 & 12 & 2090 & 1280.35 & 1.632 & 2050.66 & & & \
\hline 15 & & & & & & & & & & \
\hline 16 & & & & & & & 85564.040 & & &\
\hline 
\end{array}\)
-Refer to Exhibit 11.5. What formula should be entered in cell F7 to compute the seasonal factor using the multiplicative seasonal effects model?

Accepted Answer

A)  =$J$3*D4+(1-$J$3)*(E3+F3) 
B)  =$J$4*(D7/E7)+(1-$J$4)*F3 
C)  =$J$4*(E7/E6)+(1-$J$4)*E6 
D)  =$J$3*G3+(1-$J$3)*(D3+G3) 
A)  =$J$3*D4+(1-$J$3)*(E3+F3) 
B)  =$J$4*(D7/E7)+(1-$J$4)*F3 
C)  =$J$4*(E7/E6)+(1-$J$4)*E6 
D)  =$J$3*G3+(1-$J$3)*(D3+G3)

Question 19

Exhibit 11.7
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using Holt's method. The store has collected 12 quarters of data and needs your help to analyze the data.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|c|c|} 
\hline& \text { A } & \text { B } & \mathrm{C} & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{G} & \mathrm{H} & \mathrm{I} & \mathrm{J} \
\hline 1 & & & \text { Time } & \text { Actual } & \text { Base } & & \text { Predicted } & & & \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Trend } & \text { Sales } & & & \
\hline 3 & 1 & 1 & 1 & 284 & & & & & \text { alpha } & 0.5 \
\hline 4 & & 2 & 2 & 184 & & & & & \text { beta } & 0.5 \
\hline 5 & & 3 & 3 & 365 & 287.0 & 14.0 & 209.0 & & \
\hline 6 & & 4 & 4 & 492 & 396.5 & 61.8 & 301.0 & & & \
\hline 7 & 2 & 1 & 5 & 485 & 471.6 & 68.4 & 458.3 & & & \
\hline 8 & & 2 & 6 & 277 & 408.5 & 2.7 & 540.1 & & & \
\hline 9 & & 3 & 7 & 606 & 508.6 & 51.4 & 411.2 & & & \
\hline 10 & & 4 & 8 & 722 & 641.0 & 91.9 & 560.0 & & & \
\hline 11 & 3 & 1 & 9 & 763 & 747.9 & 99.4 & 732.9 & & & \
\hline 12 & & 2 & 10 & 593 & 720.2 & 35.8 & 847.3 & & & \
\hline 13 & & 3 & 11 & 912 & 834.0 & 74.8 & 756.0 & & & \
\hline 14 & & 4 & 12 & 1145 & 1026.9 & 133.9 & 908.8 & & & \
\hline 15 & & & & & & & & & & \
\hline 16 & & & & & & &  31877.0 & &\
\hline 
\end{array}\)

-Refer to Exhibit 11.7. What are predicted sales for time period 13 using the data in the spreadsheet?

Accepted Answer

A)  908 $\le$ predicted sales < 909 
B)  1026 $\le$ predicted sales < 1027 
C)  1144$\le$ predicted sales < 1146 
D)  1160 $\le$predicted sales < 1161 
A)  908 $\le$ predicted sales < 909 
B)  1026 $\le$ predicted sales < 1027 
C)  1144$\le$ predicted sales < 1146 
D)  1160 $\le$predicted sales < 1161

Question 20

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 H3 to compute the Seasonal Forecast value for year 1 Quarter 1?

Accepted Answer

A)  =F3*VLOOKUP(B3,$B$18:$C$21,2) 
B)  =F3*HLOOKUP(B3,$B$18:$B$21,2) 
C)  =F3*VLOOKUP(B3,$B$18:$B$21,2) 
D)  =F3*VLOOKUP(B3,$C$18:$C$21,2) 
A)  =F3*VLOOKUP(B3,$B$18:$C$21,2) 
B)  =F3*HLOOKUP(B3,$B$18:$B$21,2) 
C)  =F3*VLOOKUP(B3,$B$18:$B$21,2) 
D)  =F3*VLOOKUP(B3,$C$18:$C$21,2)

Why might we not be able to build a regression model to predict a dependent variable?

Which of the following is not a quantitative technique for evaluating the accuracy of a time-series modeling technique?

How many indicator variables are required if there are p seasons in a time series and you are forecasting with a seasonal regression model?

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

Why might we not be able to build a regression model to predict a dependent variable?

Which of the following is not a quantitative technique for evaluating the accuracy of a time-series modeling technique?

How many indicator variables are required if there are p seasons in a time series and you are forecasting with a seasonal regression model?

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