Question 1

Which of the following statements are true regarding the difference between forecasts using exponential smoothing and forecasts using a weighted moving average method?

Accepted Answer

A)  The exponential smoothing forecasts will have a steeper trend line. 
B)  The weighted moving average forecasts will form a level line of constant value. 
C)  The exponential smoothing forecasts will form a level line of constant value. 
D)  The exponential smoothing forecasts will do a better job of capturing the underlying trend in the data. 
A)  The exponential smoothing forecasts will have a steeper trend line. 
B)  The weighted moving average forecasts will form a level line of constant value. 
C)  The exponential smoothing forecasts will form a level line of constant value. 
D)  The exponential smoothing forecasts will do a better job of capturing the underlying trend in the data.

Question 2

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 2 using the data in the spreadsheet?

Accepted Answer

A)  208.5 $\le$predicted sales < 209.5 
B)  233.5 $\le$ predicted sales < 234.5 
C)  283.5 $\le$predicted sales < 284.5 
D)  300.5 $\le$ predicted sales < 301.5 
A)  208.5 $\le$predicted sales < 209.5 
B)  233.5 $\le$ predicted sales < 234.5 
C)  283.5 $\le$predicted sales < 284.5 
D)  300.5 $\le$ predicted sales < 301.5

Question 3

Project 11.2 F1F1F1S1F1F1F10 Predicting Bowling Games
Dave Cummins runs a local bowling alley. In the face of increasing competition from other local establishments, Dave has decided he must upgrade his facilities to accommodate a younger crowd. He has examined various "cosmic bowling" upgrades for his facility and has finally decided on a package. Dave has approached a local bank for financing assistance. The bank is conservative in its lending practices. As a result the loan manager would like more insight into the potential earnings of the bowling alley, with and without the upgrades. You bowl in leagues in Dave's bowling alley. You enjoy the establishment and Dave is a friend. Thus, you have offered your services to help Dave provide a reasonable projection of establishment earnings based on bowling games. Dave has provided you the following information on lines of bowling over the past five years.
 $\text { Dave's Buwling Lanes }$
$\begin{array}{|c|c|c|}
\hline \text { Year } & \text { Quarter } & \begin{array}{c}
\text { Lines of } \
\text { Bowling }
\end{array} \
\hline 1994 & \text { Summer } & 3829 \
& \text { Fall } & 3699 \
& \text { Winter } & 3555 \
& \text { Spring } & 3657 \
\hline 1995 & \text { Summer } & 3894 \
& \text { Fall } & 3778 \
& \text { Winter } & 3641 \
& \text { Spring } & 3731 \
\hline 1996 & \text { Summer } & 3987 \
& \text { Fall } & 3842 \
& \text { Winter } & 3731 \
& \text { Spring } & 3825 \
\hline 1997 & \text { Summer } & 4052 \
& \text { Fall } & 3934 \
& \text { Winter } & 3803 \
& \text { Spring } & 3892 \
\hline 1998 & \text { Summer } & 4148 \
& \text { Fall } & 4010 \
& \text { Winter } & 3880 \
& \text { Spring } & 3968 \
\hline
\end{array}$ Information from the cosmic bowling upgrade manufacturer suggests a 3-5% increase in bowling lines every year for the first 4 years after the installation of their product. Based on Dave's data develop an appropriate forecasting model. Provide Dave forecasts for the next year both with and without the cosmic bowling upgrade.

Accepted Answer

The model for this problem is a seasonal

Question 4

Exhibit 11.8
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using Winter's method. The store has collected 12 quarters of data and needs your help to analyze the data.
 \(\begin{array}{|c|c|c|c|c|c|c|c|c|} 
\hline& \mathrm{A} & \mathrm{B} & \mathrm{C} & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{G} & \mathrm{H} \
\hline 1 & & & \text { Time } & \text { Actual } & \text { Base } & & \text { Seasonal } & \text { Predicted } \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Level } & \text { Trend } & \text { Factor } & \text { Sales } \
\hline 3 & 1 & 1 & 1 & 284 & & & & \
\hline 4 & & 2 & 2 & 184 & & & & \
\hline 5 & & 3 & 3 & 365 & & & & \
\hline 6 & & 4 & 4 & 492 & & & & \
\hline 7 & 2 & 1 & 5 & 485 & & & & \
\hline 8 & & 2 & 6 & 277 & 413.5 & 20.5 & 0.567 & 217.9 \
\hline 9 & & 3 & 7 & 606 & 457.2 & 27.4 & 1.124 & 478.2 \
\hline 10 & & 4 & 8 & 722 & 484.9 & 27.5 & 1.486 & 719.7 \
\hline 11 & 3 & 1 & 9 & 763 & 579.5 & 47.6 & 0.942 & 461.1 \
\hline 12 & & 2 & 10 & 593 & 710.9 & 72.8 & 0.594 & 355.5 \
\hline 13 & & 3 & 11 & 912 & 789.2 & 74.4 & 1.127 & 881.0 \
\hline 14 & & 4 & 12 & 1145 & 845.0 & 68.8 & 1.473 & 1283.0 \
\hline 15 & & & & & & & & \
\hline 16 & & & & & & & \text { MSE } & 28,474.73 \
\hline 17 & & & \text { alpha } & 0.2 & & & & \
\hline 18 & & & \text { beta } & 0.3 & & & & \
\hline 19 & & & \text { gamma } & 0.1 & & & & \
\hline 20 & & & & & & & & \
\hline
\end{array}\)

-Refer to Exhibit 11.8. What formula should be entered in cell F7 to compute the Trend value for year 2 Quarter 1?

Accepted Answer

A)  =$D$18*(E6-E7)+(1-$D$18)*F6 
B)  =$D$18*(E7-E6)+$D$18*F6 
C)  =$D$18*(E7-E6)+(1-$D$18)*F6 
D)  =$D$18*(E7-E6)*(1-$D$18) 
A)  =$D$18*(E6-E7)+(1-$D$18)*F6 
B)  =$D$18*(E7-E6)+$D$18*F6 
C)  =$D$18*(E7-E6)+(1-$D$18)*F6 
D)  =$D$18*(E7-E6)*(1-$D$18)

Question 5

As the number of periods in the forecast, k, increases

Accepted Answer

A)  the moving average prediction will be smoother. 
B)  it is harder to get a good forecast. 
C)  the forecast will respond more quickly to changes in the data. 
D)  the moving average will increase in value. 
A)  the moving average prediction will be smoother. 
B)  it is harder to get a good forecast. 
C)  the forecast will respond more quickly to changes in the data. 
D)  the moving average will increase in value.

Question 6

Exhibit 11.1
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 moving averages.
 $\begin{array}{|c|c|c|c|} 
\hline& \text { A } & \text { B } & \text { C } \
\hline 1 & & \text { Number of } & \text { 4-Month } \
\hline 2 & \text { Time Period } & \text { Cars Sold } & \text { Moving Avg. } \
\hline 3 & 1 & 70 & \
\hline 4 & 2 & 80 & \
\hline 5 & 3 & 66 & \
\hline 6 & 4 & 74 & \
\hline 7 & 5 & 64 & \
\hline 8 & 6 & 76 & 71.00 \
\hline 9 & 7 & 72 & 70.00 \
\hline 10 & 8 & 82 & 71.50 \
\hline 11 & 9 & 82 & 73.50 \
\hline 12 & 10 & 76 & 78.00 \
\hline 13 & 11 & 84 & 78.00 \
\hline 14 & 12 & 80 & 81.00 \
\hline 15 & 13 & & \
\hline 16 & 14 & & \
\hline 17 & & & \
\hline 18 & & \text { MSE } & 40.59 \
\hline
\end{array}$

-Refer to Exhibit 11.1. What would be the forecasted values for time periods 13 and 14?

Accepted Answer

A)  81.00 and 79.50. 
B)  78.00 and 78.00. 
C)  80.50 and 80.13. 
D)  80.50 and 80.00. 
A)  81.00 and 79.50. 
B)  78.00 and 78.00. 
C)  80.50 and 80.13. 
D)  80.50 and 80.00.

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. The store wishes to use Solver to find the optimal values for cell E3. Provide the following Risk Solver Platform (RSP) settings.
Objective Cell:
Variables Cells:
Constraints Cells:

Accepted Answer

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

Question 8

Exhibit 11.13
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 moving averages.
 $$\begin{array} { | c | c | c | c | } 
\hline & \text { A } & \text { B } & \text { C } \
\hline 1 & & \text { Number of } & \text { 4-Month } \
\hline 2 & \text { Time Period } & \text { Toys Sold } & \text { Moving Avg } \
\hline 3 & 1 & 174 & \
\hline 4 & 2 & 189 & \
\hline 5 & 3 & 168 & \
\hline 6 & 4 & 180 & \
\hline 7 & 5 & 165 & 177.75 \
\hline 8 & 6 & 183 & 175.50 \
\hline 9 & 7 & 177 & 174.00 \
\hline 10 & 8 & 192 & 176.25 \
\hline 11 & 9 & 192 & 179.25 \
\hline 12 & 10 & 183 & 186.00 \
\hline 13 & 11 & 195 & 186.00 \
\hline 14 & 12 & 189 & 190.50 \
\hline 15 & & & \
\hline 16 & & \mathbf { M S E } & 91.34 \
\hline
\end{array}$$
-Refer to Exhibit 11.13. What formulas go into cells B7:B9 of the following partial spreadsheet where data for periods 9-12 represent actual data?

Accepted Answer

The answer of Exhibit 11.13
The following questions use the data...

Question 9

Which of the following describes an additive seasonal effect in times series data?

Accepted Answer

A)  An occasional pattern of equal magnitude. 
B)  An occasional pattern of unequal magnitude. 
C)  A regular, repeating pattern of equal magnitude. 
D)  A regular, repeating pattern of increasing magnitude. 
A)  An occasional pattern of equal magnitude. 
B)  An occasional pattern of unequal magnitude. 
C)  A regular, repeating pattern of equal magnitude. 
D)  A regular, repeating pattern of increasing magnitude.

Question 10

The general form of an extrapolation model for time-series analysis is

Accepted Answer

A)  t+1 = f(Xt, Y1, Z2, ...) 
B)  t = f(Yt, YtF1F1F1S1F1F1F101, YtF1F1F1S1F1F1F102, ...) 
C)  Yt+1 = f(Yt, YtF1F1F1S1F1F1F101, YtF1F1F1S1F1F1F102, ...) 
D)  t+1 = f(Yt, YtF1F1F1S1F1F1F101, YtF1F1F1S1F1F1F102, ...) 
A)  t+1 = f(Xt, Y1, Z2, ...) 
B)  t = f(Yt, YtF1F1F1S1F1F1F101, YtF1F1F1S1F1F1F102, ...) 
C)  Yt+1 = f(Yt, YtF1F1F1S1F1F1F101, YtF1F1F1S1F1F1F102, ...) 
D)  t+1 = f(Yt, YtF1F1F1S1F1F1F101, YtF1F1F1S1F1F1F102, ...)

Question 11

Exhibit 11.19
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 double moving average method.
  
-Refer to Exhibit 11.19. What are the forecasts for time periods 13-16?

Accepted Answer

The answer of Exhibit 11.19
The following questions use the data...

Question 12

Exhibit 11.6
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 double moving average model with k = 4.
  
-Refer to Exhibit 11.6. What formula should be entered in cell H9 to compute the trend using the double moving average model with k = 4?

Accepted Answer

A)  =2*(AVERAGE(E9,F9))/4 
B)  =2*(E9-F9)/(4-1) 
C)  =2*(E9-F9)/(4*2) 
D)  =2*(D9-F9)/(4-1) 
A)  =2*(AVERAGE(E9,F9))/4 
B)  =2*(E9-F9)/(4-1) 
C)  =2*(E9-F9)/(4*2) 
D)  =2*(D9-F9)/(4-1)

Question 13

Exhibit 11.23
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 a quadratic trend model to forecast sales.
 $\begin{array}{|l|r|}
\hline {\text { Regression Statistics }} \
\hline & \text { Coefficients } \
\hline \text { Intercept } & 56.29 \
\hline \text { X Variable 1 } & 3.59 \
\hline \text { X Variable 2 } & 0.08 \
\hline
\end{array}$
 $\begin{array}{|c|c|c|c|c|c|c|} 
\hline & \text { A } & \text { B } & \text { C } & \text { D } & \text { E } & F \
\hline 1 & & & \text { Time } & & \text { Actual } & \text { Quadratic } \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Time } 2 & \text { Sales } & \text { Trend } \
\hline 3 & 1 & 1 & 1 & 1 & 55.2 & 60.0 \
\hline 4 & & 2 & 2 & 4 & 60.0 & 63.8 \
\hline 5 & & 3 & 3 & 9 & 86.4 & 67.8 \
\hline 6 & & 4 & 4 & 16 & 74.4 & 71.9 \
\hline 7 & 2 & 1 & 5 & 25 & 62.4 & 76.2 \
\hline 8 & & 2 & 6 & 36 & 67.2 & 80.7 \
\hline 9 & & 3 & 7 & 49 & 115.2 & 85.3 \
\hline 10 & & 4 & 8 & 64 & 86.4 & 90.1 \
\hline 11 & 3 & 1 & 9 & 81 & 74.4 & 95.1 \
\hline 12 & & 2 & 10 & 100 & 100.8 & 100.2 \
\hline 13 & & 3 & 11 & 121 & 127.2 & 105.5 \
\hline 14 & & 4 & 12 & 144 & 103.2 & 110.9 \
\hline 15 & & & 13 & 169 & & 116.5\
\hline 
\end{array}$

-Refer to Exhibit 11.23. Based on the regression output, what formulas should go in cells D3:F14?

Accepted Answer

The answer of Exhibit 11.23
The following questions use the data...

Question 14

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 G12 to compute the forecast for time period 10?

Accepted Answer

A)  =E10+F7 
B)  =E12+F12 
C)  =E12+F8 
D)  =E11+F8 
A)  =E10+F7 
B)  =E12+F12 
C)  =E12+F8 
D)  =E11+F8

Question 15

Exhibit 11.1
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 moving averages.
 $\begin{array}{|c|c|c|c|} 
\hline& \text { A } & \text { B } & \text { C } \
\hline 1 & & \text { Number of } & \text { 4-Month } \
\hline 2 & \text { Time Period } & \text { Cars Sold } & \text { Moving Avg. } \
\hline 3 & 1 & 70 & \
\hline 4 & 2 & 80 & \
\hline 5 & 3 & 66 & \
\hline 6 & 4 & 74 & \
\hline 7 & 5 & 64 & \
\hline 8 & 6 & 76 & 71.00 \
\hline 9 & 7 & 72 & 70.00 \
\hline 10 & 8 & 82 & 71.50 \
\hline 11 & 9 & 82 & 73.50 \
\hline 12 & 10 & 76 & 78.00 \
\hline 13 & 11 & 84 & 78.00 \
\hline 14 & 12 & 80 & 81.00 \
\hline 15 & 13 & & \
\hline 16 & 14 & & \
\hline 17 & & & \
\hline 18 & & \text { MSE } & 40.59 \
\hline
\end{array}$

-Refer to Exhibit 11.1. What is the 4-month moving average forecast for month 5?

Accepted Answer

A)  71 
B)  72.5 
C)  74 
D)  75 
A)  71 
B)  72.5 
C)  74 
D)  75

Question 16

Exhibit 11.1
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 moving averages.
 $\begin{array}{|c|c|c|c|} 
\hline& \text { A } & \text { B } & \text { C } \
\hline 1 & & \text { Number of } & \text { 4-Month } \
\hline 2 & \text { Time Period } & \text { Cars Sold } & \text { Moving Avg. } \
\hline 3 & 1 & 70 & \
\hline 4 & 2 & 80 & \
\hline 5 & 3 & 66 & \
\hline 6 & 4 & 74 & \
\hline 7 & 5 & 64 & \
\hline 8 & 6 & 76 & 71.00 \
\hline 9 & 7 & 72 & 70.00 \
\hline 10 & 8 & 82 & 71.50 \
\hline 11 & 9 & 82 & 73.50 \
\hline 12 & 10 & 76 & 78.00 \
\hline 13 & 11 & 84 & 78.00 \
\hline 14 & 12 & 80 & 81.00 \
\hline 15 & 13 & & \
\hline 16 & 14 & & \
\hline 17 & & & \
\hline 18 & & \text { MSE } & 40.59 \
\hline
\end{array}$

-Refer to Exhibit 11.1. If predicting the cars sold for time period 14, what formula must be placed in cell B16?

Accepted Answer

A)  =AVERAGE(B12:B15) 
B)  =AVERAGE(B12:B15)/4 
C)  =TREND(B12:B15) 
D)  =B14 
A)  =AVERAGE(B12:B15) 
B)  =AVERAGE(B12:B15)/4 
C)  =TREND(B12:B15) 
D)  =B14

Question 17

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 I3 to compute the Seasonal Value for year 1 Quarter 1?

Accepted Answer

A)  =388.88+10.052*C3+4.248*D3+79.917*E3+296.008*F3+84.924*G3 
B)  =10.052*C3+4.248*D3-79.917*E3-296.008*F3-84.924*G3 
C)  =388.88+10.052*C3+4.248*D3-79.917*E3-296.008*F3-84.924*G3 
D)  =I3+10.052*C3+4.248*D3-79.917*E3-296.008*F3-84.924*G3 
A)  =388.88+10.052*C3+4.248*D3+79.917*E3+296.008*F3+84.924*G3 
B)  =10.052*C3+4.248*D3-79.917*E3-296.008*F3-84.924*G3 
C)  =388.88+10.052*C3+4.248*D3-79.917*E3-296.008*F3-84.924*G3 
D)  =I3+10.052*C3+4.248*D3-79.917*E3-296.008*F3-84.924*G3

Question 18

Exhibit 11.25
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 a seasonal regression model to forecast sales.
 $\begin{array}{|l|r|}
\hline {\text { Regression Statistics }} \
\hline & \text { Coefficients } \
\hline \text { Intercept } & 60.42 \
\hline \text { X Variable 1 } & 1.91 \
\hline \text { X Variable 2 } & 0.16 \
\hline \text { X Variable 3 } & -11.85 \
\hline \text { X Variable 4 } & -3.57 \
\hline \text { X Variable 5 } & 25.98 \
\hline
\end{array}$

-Refer to Exhibit 11.25. Based on the regression output what formulas should go in cells D3:I14?

Accepted Answer

The answer of Exhibit 11.25
The following questions use the data...

Question 19

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 are predicted sales for the first quarter of year 4?

Accepted Answer

A)  1155 F1F1F1S1?F1F1F10 predicted sales < 1160 
B)  1065 F1F1F1S1?F1F1F10 predicted sales < 1070 
C)  1410 F1F1F1S1?F1F1F10 predicted sales < 1415 
D)  1635 F1F1F1S1?F1F1F10 predicted sales < 1640 
A)  1155 F1F1F1S1?F1F1F10 predicted sales < 1160 
B)  1065 F1F1F1S1?F1F1F10 predicted sales < 1070 
C)  1410 F1F1F1S1?F1F1F10 predicted sales < 1415 
D)  1635 F1F1F1S1?F1F1F10 predicted sales < 1640

Question 20

Exhibit 11.9
The following questions use the data below.
Joe's Sporting Goods wants to forecast quarterly sales figures using a linear 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.
 $$\begin{array}{l}
\text { Rogression Stafisties }\
\begin{array} { | l | r | } 
\hline & \text { Caffieients } \
\hline \text { Interegt } & 114.136 \
\hline \mathrm { X } \text { Variable } & \mathbf { 6 9 . 9 7 9 } \
\hline
\end{array}
\end{array}$$ $\begin{array}{|c|c|c|c|c|c|} 
\hline& \text { A } & \text { B } & \text { C } & \text { D } & \text { E } \
\hline 1 & & & \text { Time } & \text { Actual } & \text { Linear } \
\hline 2 & \text { Year } & \text { Qtr } & \text { Period } & \text { Sales } & \text { Trend } \
\hline 3 & 1 & 1 & 1 & 284 & \
\hline 4 & & 2 & 2 & 184 & 254.1 \
\hline 5 & & 3 & 3 & 365 & 324.1 \
\hline 6 & & 4 & 4 & 492 & 394.1 \
\hline 7 & 2 & 1 & 5 & 485 & 464.0 \
\hline 8 & & 2 & 6 & 277 & 534.0 \
\hline 9 & & 3 & 7 & 606 & 604.0 \
\hline 10 & & 4 & 8 & 722 & 674.0 \
\hline 11 & 3 & 1 & 9 & 763 & 743.9 \
\hline 12 & & 2 & 10 & 593 & 813.9 \
\hline 13 & & 3 & 11 & 912 & 883.9 \
\hline 14 & & 4 & 12 & 1145 & 953.9\
\hline 
\end{array}$

-Refer to Exhibit 11.9. Which column in the spreadsheet represents the independent variable for a regression model?

Accepted Answer

A)  A 
B)  B 
C)  C 
D)  D 
A)  A 
B)  B 
C)  C 
D)  D

Which of the following statements are true regarding the difference between forecasts using exponential smoothing and forecasts using a weighted moving average method?

As the number of periods in the forecast, k, increases

Which of the following describes an additive seasonal effect in times series data?

The general form of an extrapolation model for time-series analysis is

Exhibit 11.19 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 double moving average method. -Refer to Exhibit 11.19. What are the forecasts for time periods 13-16?

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

Exam 11: Time Series Forecasting

Which of the following statements are true regarding the difference between forecasts using exponential smoothing and forecasts using a weighted moving average method?

As the number of periods in the forecast, k, increases

Which of the following describes an additive seasonal effect in times series data?

The general form of an extrapolation model for time-series analysis is

Exhibit 11.19 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 double moving average method. -Refer to Exhibit 11.19. What are the forecasts for time periods 13-16?

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