Deck 5: Forecasting
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Deck 5: Forecasting
1
Qualitative models produce forecasts that are a little better than simple guesses or coin tosses.
False
2
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).
False
3
A trend-projection forecasting method is a causal forecasting method.
False
4
A moving average forecasting method is a causal forecasting method.
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5
The Delphi method solicits input from customers or potential customers regarding their future purchasing plans.
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6
TIME SERIES models rely on judgment in an attempt to incorporate qualitative or subjective factors into the forecasting model.
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7
The fewer the periods over which one takes a moving average,the more accurately the resulting forecast mirrors the actual data of the most recent time periods.
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8
TIME SERIES models attempt to predict the future by using historical data.
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9
Mean absolute deviation (MAD)is simply the sum of forecast errors.
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10
A scatter diagram is useful to determine if a relationship exists between two variables.
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11
Regression is always a superior forecasting method to exponential smoothing,so regression should be used whenever the appropriate software is available.
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12
TIME SERIES models enable the forecaster to include specific representations of various qualitative and quantitative factors.
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13
Four components of time series are trend,moving average,exponential smoothing,and seasonality.
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14
The most common quantitative causal model is regression analysis.
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15
A medium-term forecast typically covers a two- to four-year time horizon.
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16
The three categories of forecasting models are time series,quantitative,and qualitative.
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17
In a weighted moving average,the weights assigned must sum to 1.
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18
An exponential forecasting method is a TIME SERIES forecasting method.
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19
Qualitative models attempt to incorporate judgmental or subjective factors into the forecasting model.
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20
The naïve forecast for the next period is the actual value observed in the current period.
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21
Multiple regression can be used to develop a multiplicative decomposition model.
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22
Exponential smoothing cannot be used for data with a trend.
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23
A graphical plot with sales on the Y axis and time on the X axis is a
A)scatter diagram.
B)trend projection.
C)radar chart.
D)line graph.
E)bar chart.
A)scatter diagram.
B)trend projection.
C)radar chart.
D)line graph.
E)bar chart.
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24
A seasonal index of 1 means that the season is average.
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25
Scatter diagrams can be useful in spotting trends or cycles in data over time.
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26
Which of the following is not classified as a qualitative forecasting model?
A)exponential smoothing
B)Delphi method
C)jury of executive opinion
D)sales force composite
E)consumer market survey
A)exponential smoothing
B)Delphi method
C)jury of executive opinion
D)sales force composite
E)consumer market survey
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27
The process of isolating linear trend and seasonal factors to develop a more accurate forecast is called regression.
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28
A seasonal index must be between -1 and +1.
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29
Which of the following is a technique used to determine forecasting accuracy?
A)exponential smoothing
B)moving average
C)regression
D)Delphi method
E)mean absolute percent error
A)exponential smoothing
B)moving average
C)regression
D)Delphi method
E)mean absolute percent error
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30
When the smoothing constant α = 0,the exponential smoothing model is equivalent to the naïve forecasting model.
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31
Multiple regression may be used to forecast both trend and seasonal components present in a time series.
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32
Which of the following statements about scatter diagrams is true?
A)Time is always plotted on the y-axis.
B)It can depict the relationship among three variables simultaneously.
C)It is helpful when forecasting with qualitative data.
D)The variable to be forecasted is placed on the y-axis.
E)It is not a good tool for understanding TIME SERIES data.
A)Time is always plotted on the y-axis.
B)It can depict the relationship among three variables simultaneously.
C)It is helpful when forecasting with qualitative data.
D)The variable to be forecasted is placed on the y-axis.
E)It is not a good tool for understanding TIME SERIES data.
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33
Multiple regression models use dummy variables to adjust for seasonal variations in an additive TIME SERIES model.
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34
When the smoothing constant α = 1,the exponential smoothing model is equivalent to the naïve forecasting model.
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35
An advantage of exponential smoothing over a simple moving average is that exponential smoothing requires one to retain less data.
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36
Which of the following is considered a causal method of forecasting?
A)exponential smoothing
B)moving average
C)Holt's method
D)Delphi method
E)None of the above
A)exponential smoothing
B)moving average
C)Holt's method
D)Delphi method
E)None of the above
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37
In a second order exponential smoothing,a low β gives less weight to more recent trends.
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38
A judgmental forecasting technique that uses decision makers,staff personnel,and respondent to determine a forecast is called
A)exponential smoothing.
B)the Delphi method.
C)jury of executive opinion.
D)sales force composite.
E)consumer market survey.
A)exponential smoothing.
B)the Delphi method.
C)jury of executive opinion.
D)sales force composite.
E)consumer market survey.
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39
Adaptive smoothing is analogous to exponential smoothing where the coefficients α and β are periodically updated to improve the forecast.
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40
Bias is the average error of a forecast model.
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41
Which of the following methods produces a particularly stiff penalty in periods with large forecast errors?
A)MAD
B)MSE
C)MAPE
D)decomposition
E)bias
A)MAD
B)MSE
C)MAPE
D)decomposition
E)bias
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42
Enrollment in a particular class for the last four semesters has been 120,126,110,and 130 (listed from oldest to most recent).Develop a forecast of enrollment next semester using exponential smoothing with an alpha = 0.2.Assume that an initial forecast for the first semester was 120 (so the forecast and the actual were the same).
A)118.96
B)121.17
C)130
D)120
E)None of the above
A)118.96
B)121.17
C)130
D)120
E)None of the above
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43
A TIME SERIES forecasting model in which the forecast for the next period is the actual value for the current period is the
A)Delphi model.
B)Holt's model.
C)naïve model.
D)exponential smoothing model.
E)weighted moving average.
A)Delphi model.
B)Holt's model.
C)naïve model.
D)exponential smoothing model.
E)weighted moving average.
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44
Assume that you have tried three different forecasting models.For the first,the MAD = 2.5,for the second,the MSE = 10.5,and for the third,the MAPE = 2.7.We can then say:
A)the third method is the best.
B)the second method is the best.
C)methods one and three are preferable to method two.
D)method two is least preferred.
E)None of the above
A)the third method is the best.
B)the second method is the best.
C)methods one and three are preferable to method two.
D)method two is least preferred.
E)None of the above
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45
Enrollment in a particular class for the last four semesters has been 122,128,100,and 155 (listed from oldest to most recent).The best forecast of enrollment next semester,based on a three-semester moving average,would be
A)116.7.
B)126.3.
C)168.3.
D)135.0.
E)127.7.
A)116.7.
B)126.3.
C)168.3.
D)135.0.
E)127.7.
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46
Daily demand for newspapers for the last 10 days has been as follows: 12,13,16,15,12,18,14,12,13,15 (listed from oldest to most recent).Forecast sales for the next day using a two-day weighted moving average where the weights are 3 and 1.
A)14.5
B)13.5
C)14
D)12.25
E)12.75
A)14.5
B)13.5
C)14
D)12.25
E)12.75
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47
Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100,120,115,and 123.The actual results over the 4-month period were as follows: 110,114,119,115.What was the MAD of the 4-month forecast?
A)0
B)5
C)7
D)108
E)None of the above
A)0
B)5
C)7
D)108
E)None of the above
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48
Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100,120,115,and 123.The actual results over the 4-month period were as follows: 110,114,119,115.What was the MSE of the 4-month forecast?
A)0
B)5
C)7
D)108
E)None of the above
A)0
B)5
C)7
D)108
E)None of the above
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49
Daily demand for newspapers for the last 10 days has been as follows: 12,13,16,15,12,18,14,12,13,15 (listed from oldest to most recent).Forecast sales for the next day using a two-day moving average.
A)14
B)13
C)15
D)28
E)12.5
A)14
B)13
C)15
D)28
E)12.5
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50
Which of the following methods tells whether the forecast tends to be too high or too low?
A)MAD
B)MSE
C)MAPE
D)decomposition
E)bias
A)MAD
B)MSE
C)MAPE
D)decomposition
E)bias
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51
Which of the following statements about the decomposition method is/are false?
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.
E)Decomposition can involve additive or multiplicative methods with respect to seasonality.
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.
E)Decomposition can involve additive or multiplicative methods with respect to seasonality.
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52
Daily demand for newspapers for the last 10 days has been as follows: 12,13,16,15,12,18,14,12,13,15 (listed from oldest to most recent).Forecast sales for the next day using a three-day weighted moving average where the weights are 3,1,and 1 (the highest weight is for the most recent number).
A)12.8
B)13.0
C)70.0
D)14.0
E)None of the above
A)12.8
B)13.0
C)70.0
D)14.0
E)None of the above
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53
A medium-term forecast is considered to cover what length of time?
A)2-4 weeks
B)1 month to 1 year
C)2-4 years
D)5-10 years
E)20 years
A)2-4 weeks
B)1 month to 1 year
C)2-4 years
D)5-10 years
E)20 years
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54
Which of the following is not considered to be one of the components of a time series?
A)trend
B)seasonality
C)variance
D)cycles
E)random variations
A)trend
B)seasonality
C)variance
D)cycles
E)random variations
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55
Demand for soccer balls at a new sporting goods store is forecasted using the following regression equation: Y = 98 + 2.2X where X is the number of months that the store has been in existence.Let April be represented by
X = 4.April is assumed to have a seasonality index of 1.15.What is the forecast for soccer ball demand for the month of April (rounded to the nearest integer)?
A)123
B)107
C)100
D)115
E)None of the above
X = 4.April is assumed to have a seasonality index of 1.15.What is the forecast for soccer ball demand for the month of April (rounded to the nearest integer)?
A)123
B)107
C)100
D)115
E)None of the above
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56
Which of the following methods gives an indication of the percentage of forecast error?
A)MAD
B)MSE
C)MAPE
D)decomposition
E)bias
A)MAD
B)MSE
C)MAPE
D)decomposition
E)bias
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57
As one increases the number of periods used in the calculation of a moving average,
A)greater emphasis is placed on more recent data.
B)less emphasis is placed on more recent data.
C)the emphasis placed on more recent data remains the same.
D)it requires a computer to automate the calculations.
E)one is usually looking for a long-term prediction.
A)greater emphasis is placed on more recent data.
B)less emphasis is placed on more recent data.
C)the emphasis placed on more recent data remains the same.
D)it requires a computer to automate the calculations.
E)one is usually looking for a long-term prediction.
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58
The process of isolating linear trend and seasonal factors to develop more accurate forecasts is called
A)regression.
B)decomposition.
C)smoothing.
D)monitoring.
E)None of the above
A)regression.
B)decomposition.
C)smoothing.
D)monitoring.
E)None of the above
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59
Enrollment in a particular class for the last four semesters has been 120,126,110,and 130.Suppose a one-semester moving average was used to forecast enrollment (this is sometimes referred to as a naïve forecast).Thus,the forecast for the second semester would be 120,for the third semester it would be 126,and for the last semester it would be 110.What would the MSE be for this situation?
A)196.00
B)230.67
C)100.00
D)42.00
E)None of the above
A)196.00
B)230.67
C)100.00
D)42.00
E)None of the above
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60
When is the exponential smoothing model equivalent to the naïve forecasting model?
A)α = 0
B)α = 0.5
C)α = 1
D)during the first period in which it is used
E)never
A)α = 0
B)α = 0.5
C)α = 1
D)during the first period in which it is used
E)never
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61
For the data below:
(a)Develop a scatter diagram.
(b)Compute a three-month moving average.
(c)Compute the MSE.

(b)Compute a three-month moving average.
(c)Compute the MSE.
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62
Using the additive decomposition model,what would be the period 2,Q3 forecast using the following equation:
= 20 + 3.2X1 + 1.5X2 + 0.8X3 + 0.6X4?
A)23.2
B)25
C)27
D)27.2
E)27.9

A)23.2
B)25
C)27
D)27.2
E)27.9
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63
Which of the following is not considered one of the steps to developing the decomposition method?
A)compute seasonal indices using CMAs
B)deseasonalize the data by dividing each number by its seasonal index
C)find the equation of the trend line using the deseasonlized data
D)forecast for future periods using the trend line
E)add the seasonal index to the trend forecast
A)compute seasonal indices using CMAs
B)deseasonalize the data by dividing each number by its seasonal index
C)find the equation of the trend line using the deseasonlized data
D)forecast for future periods using the trend line
E)add the seasonal index to the trend forecast
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64
A method to measure how well predictions fit actual data is
A)decomposition
B)smoothing
C)tracking signal
D)regression
E)moving average
A)decomposition
B)smoothing
C)tracking signal
D)regression
E)moving average
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65
A tracking signal was calculated for a particular set of demand forecasts.This tracking signal was positive.This would indicate that
A)demand is greater than the forecast.
B)demand is less than the forecast.
C)demand is equal to the forecast.
D)the MAD is negative.
E)None of the above
A)demand is greater than the forecast.
B)demand is less than the forecast.
C)demand is equal to the forecast.
D)the MAD is negative.
E)None of the above
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66
Which of the following is not a characteristic of trend projections?
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.
E)They are often developed using linear regression.
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.
E)They are often developed using linear regression.
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67
In the exponential smoothing with trend adjustment forecasting method,β is the
A)slope of the trend line.
B)new forecast.
C)Y-axis intercept.
D)independent variable.
E)trend smoothing constant.
A)slope of the trend line.
B)new forecast.
C)Y-axis intercept.
D)independent variable.
E)trend smoothing constant.
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68
The following table represents the new members that have been acquired by a fitness center.
Assuming α = 0.3,β = 0.4,an initial forecast of 40 for January,and an initial trend adjustment of 0 for January,use exponential smoothing with trend adjustment to come up with a forecast for May on new members.

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69
The errors in a particular forecast are as follows: 4,-3,2,5,-1.What is the tracking signal of the forecast?
A)0.4286
B)2.3333
C)5
D)1.4
E)2.5
A)0.4286
B)2.3333
C)5
D)1.4
E)2.5
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70
The computer monitoring of tracking signals and self-adjustment is referred to as
A)exponential smoothing.
B)adaptive smoothing.
C)trend projections.
D)trend smoothing.
E)running sum of forecast errors (RFSE).
A)exponential smoothing.
B)adaptive smoothing.
C)trend projections.
D)trend smoothing.
E)running sum of forecast errors (RFSE).
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71
Use simple exponential smoothing with α = 0.3 to forecast battery sales for February through May.Assume that the forecast for January was for 22 batteries. 

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72
Demand for a particular type of battery fluctuates from one week to the next.A study of the last six weeks provides the following demands (in dozens): 4,5,3,2,8,10 (last week).
(a)Forecast demand for the next week using a two-week moving average.
(b)Forecast demand for the next week using a three-week moving average.
(a)Forecast demand for the next week using a two-week moving average.
(b)Forecast demand for the next week using a three-week moving average.
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73
For the data below:
(a)Develop a scatter diagram.
(b)Develop a six-year moving average forecast.
(c)Find MAPE.

(b)Develop a six-year moving average forecast.
(c)Find MAPE.
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74
For the data below:
(a)Develop a scatter diagram.
(b)Develop a three-month moving average.
(c)Compute MAD.

(b)Develop a three-month moving average.
(c)Compute MAD.
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75
Average starting salaries for students using a placement service at a university have been steadily increasing.A study of the last four graduating classes indicates the following average salaries: $30,000,$32,000,$34,500,and $36,000 (last graduating class).Predict the starting salary for the next graduating class using a simple exponential smoothing model with α = 0.25.Assume that the initial forecast was $30,000 (so that the forecast and the actual were the same).
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76
Use simple exponential smoothing with α = 0.33 to forecast the tire sales for February through May.Assume that the forecast for January was for 22 sets of tires. 

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77
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.
(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.
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78
In picking the smoothing constant for an exponential smoothing model,we should look for a value that
A)produces a nice-looking curve.
B)equals the utility level that matches with our degree of risk aversion.
C)produces values which compare well with actual values based on a standard measure of error.
D)causes the least computational effort.
E)None of the above
A)produces a nice-looking curve.
B)equals the utility level that matches with our degree of risk aversion.
C)produces values which compare well with actual values based on a standard measure of error.
D)causes the least computational effort.
E)None of the above
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79
A seasonal index of ________ indicates that the season is average.
A)10
B)100
C)0.5
D)0
E)1
A)10
B)100
C)0.5
D)0
E)1
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80
If the Q1 demand for a particular year is 200 and the seasonal index is 0.85,what is the deseasonalized demand value for Q1?
A)170
B)185
C)215
D)235.29
E)250
A)170
B)185
C)215
D)235.29
E)250
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