Deck 12: Forecasting

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سؤال
Forecasting customer demand is rarely a key to providing good quality service.
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سؤال
A correlation coefficient is a measure of the strength of the linear relationship between an independent and a dependent variable.
سؤال
The most common type of forecasting method for long-term strategic planning is based on quantitative modeling
سؤال
A linear regression model that relates demand to time is known as a linear trend line.
سؤال
Forecast bias is measured by the per-period average of the sum of the forecast errors.
سؤال
One reason time series methods are popular for forecasting is that they are relatively easy to use and understand.
سؤال
The larger the mean absolute deviation (MAD)the more accurate the forecast.
سؤال
A gradual,long-term up or down movement of demand is referred to as a trend.
سؤال
The Delphi method generates forecasts based on informed judgments and opinions from knowledgeable individuals.
سؤال
Time series methods use historical data to predict future demand.
سؤال
The average,absolute difference between the forecast and demand is a popular measure of forecast error.
سؤال
The type of forecasting method used depends entirely whether the supply chain is continuous replenishment or not.
سؤال
Forecasts based on mathematical formulas are referred to as qualitative forecasts.
سؤال
Exponential smoothing is an averaging method for forecasting that reacts more strongly to recent changes in demand.
سؤال
A gradual,long-term up or down movement of demand is called a trend.
سؤال
Qualitative forecasts use mathematical techniques and statistical formulas.
سؤال
One way to deal with the bullwhip effect is to develop and share the forecasts with other supply chain members.
سؤال
Linear regression relates two variables using a linear model.
سؤال
Continuous replenishment systems rely heavily on extremely accurate long-term forecasts.
سؤال
A seasonal pattern is an oscillating movement in demand that occurs periodically over the short-run and is repetitive.
سؤال
Correlation in linear regression is a measure of the strength of the relationship between the dependent variable,demand,and an independent (explanatory)variable.
سؤال
The demand behavior for skis is considered cyclical.
سؤال
Movements in demand that do not follow a given pattern are referred to as random variations.
سؤال
The trend toward continuous replenishment in supply chain design has shifted the need for accurate forecasts from short-term to long-term.
سؤال
Because of advances in technology,many service industries no longer require accurate forecasts to provide high quality service.
سؤال
The type of forecasting method selected depends on time frame,demand behavior and causes of behavior.
سؤال
Because of ease of use and simplicity,exponential smoothing is preferred over smoothing average.
سؤال
Because of the development of advanced forecasting models managers no longer track forecast error.
سؤال
Long-range qualitative forecasts are used to determine future demand for new products,markets and customers.
سؤال
The moving average method is used for creating forecasts when there is no variation in demand.
سؤال
Sharing demand forecasts with supply chain members has resulted in an increased bullwhip effect.
سؤال
Short-midrange forecasts tend to use quantitative models that forecast demand based on historical demand.
سؤال
In today competitive environment,effective supply chain management requires accurate demand forecasts.
سؤال
Regression is used for forecasting when there is a relationship between the dependent variable,demand,and one or more independent (explanatory)variables.
سؤال
The long-term strategic planning process is dependent upon qualitative forecasting methods.
سؤال
Because of globalization of markets,managers are finding it increasingly more difficult to create accurate demand forecasts.
سؤال
Because of the heightened competition resulting from globalization most companies find little strategic value in long-range forecast.
سؤال
Time series methods assume that demand patterns in the past is a good predictor of demand in the future.
سؤال
Many companies are shifting from long-term to short-term forecast for strategic planning.
سؤال
Multiple regression analysis can be used to relate demand to two or more dependent variables.
سؤال
A long-range forecast would normally not be used to

A)design the supply chain.
B)implement strategic programs.
C)determine production schedules.
D)plan new products for changing markets
سؤال
A ___________ is an up-and-down movement in demand that repeats itself over a lengthy time period of more than a year.

A)trend
B)seasonal pattern
C)random variation
D)cycle
سؤال
An exponential smoothing forecasting technique requires all of the following except

A)the forecast for the current period.
B)the actual demand for the current period.
C)a smoothing constant.
D)large amounts of historical demand data.
سؤال
The weighted moving average forecast for the fifth period with weights of 0.15 for period 1,0.20 for period 2,0.25 for period 3,and 0.40 for period 4,using the demand data shown below is
<strong>The weighted moving average forecast for the fifth period with weights of 0.15 for period 1,0.20 for period 2,0.25 for period 3,and 0.40 for period 4,using the demand data shown below is  </strong> A)3760 B)3700 C)3650 D)3325 <div style=padding-top: 35px>

A)3760
B)3700
C)3650
D)3325
سؤال
The _________________ forecast method consists of an exponentially smoothed forecast with a trend adjustment factor added to it.

A)Exponentially smoothed
B)Adjusted exponentially smoothed
C)Time series
D)Moving average
سؤال
The per period average of cumulative error is called

A)cumulative forecast variation.
B)absolute error.
C)average error.
D)noise.
سؤال
The sum of the weights in a weighted moving average forecast

A)must equal the number of periods being averaged.
B)must equal 1.00.
C)must be less than 1.00.
D)must be greater than 1.00.
سؤال
Which of the following is not a type of predictable demand behavior?

A)trend
B)random variation
C)cycle
D)seasonal pattern
سؤال
The smoothing constant,α,in the exponential smoothing forecast

A)must always be a value greater than 1.0.
B)must always be a value less than 0.10.
C)must be a value between 0.0 and 1.0.
D)should be equal to the time frame for the forecast.
سؤال
Given the following demand data for the past five months,the three period moving average forecast for June is
<strong>Given the following demand data for the past five months,the three period moving average forecast for June is  </strong> A)103.33. B)99.00. C)95.00. D)92.50 <div style=padding-top: 35px>

A)103.33.
B)99.00.
C)95.00.
D)92.50
سؤال
The closer the smoothing constant,α,is to 1.0

A)the greater the reaction to the most recent demand.
B)the greater the dampening,or smoothing,effect.
C)the more accurate the forecast.
D)the less accurate the forecast.
سؤال
Regression forecasting methods relate _________to other factors that cause demand behavior.

A)Supply
B)Demand
C)Time
D)Money
E)Efficiency
سؤال
Selecting the type of forecasting method to use depends on

A)the time frame of the forecast.
B)the behavior of demand and demand patterns.
C)the causes of demand behavior.
D)all of the above.
سؤال
Forecast methods based on judgment,opinion,past experiences,or best guesses are known as ___________ methods.

A)quantitative
B)qualitative
C)time series
D)regression
سؤال
A qualitative procedure used to develop a consensus forecast is known as

A)exponential smoothing.
B)regression methods.
C)the Delphi technique.
D)naïve forecasting.
سؤال
Given the following demand data for the past five months,the four period moving average forecast for June is
<strong>Given the following demand data for the past five months,the four period moving average forecast for June is  </strong> A)96.25. B)99.00. C)110.00. D)93.75. <div style=padding-top: 35px>

A)96.25.
B)99.00.
C)110.00.
D)93.75.
سؤال
The exponential smoothing model produces a naïve forecast when the smoothing constant,α,is equal to

A)0.00.
B)1.00.
C)0.50.
D)2.00
سؤال
A forecast where the current period's demand is used as the next period's forecast is known as a

A)moving average forecast.
B)naïve forecast.
C)weighted moving average forecast.
D)Delphi forecast.
سؤال
A company wants to product a weighted moving average forecast for April with the weights 0.40,0.35,and 0.25 assigned to March,February,and January,respectively.If the company had demands of 5,000 in January,4,750 in February,and 5,200 in March,then April's forecast is

A)4983.33.
B)4992.50.
C)4962.50.
D)5000.00.
سؤال
The _______ method uses demand in the first period to forecast demand in the next period.

A)naïve
B)moving average
C)exponential smoothing.
D)linear trend
سؤال
The mean absolute percentage deviation (MAPD)measures the absolute error as a percentage of

A)all errors.
B)per period demand.
C)total demand.
D)the average error.
سؤال
A tracking signal is computed by

A)multiplying the cumulative error by MAD
B)multiplying the absolute error by MAD
C)dividing MAD by the cumulative absolute error
D)dividing the cumulative error by MAD
سؤال
Which of the following is a reason why a forecast can go "out of control?"

A)a change in trend
B)an irregular variation such as unseasonable weather
C)a promotional campaign
D)all of the above
سؤال
A mathematical technique for forecasting that relates the dependent variable to an independent variable is

A)correlation analysis.
B)exponential smoothing.
C)linear regression.
D)weighted moving average.
سؤال
Given the demand and forecast values shown in the table below:
<strong>Given the demand and forecast values shown in the table below:   The exponential smoothing forecast for November using α = 0.35 is</strong> A)552.45. B)553.50. C)554.55. D)557.50. <div style=padding-top: 35px>
The exponential smoothing forecast for November using α = 0.35 is

A)552.45.
B)553.50.
C)554.55.
D)557.50.
سؤال
Which of the following statements concerning average error is true?

A)a positive value indicates high bias,and a negative value indicates low bias
B)a positive value indicates zero bias,and a negative value indicates low bias
C)a negative value indicates zero bias,and a negative value indicates high bias
D)a positive value indicates low bias,and a negative value indicates high bias
سؤال
For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is
<strong>For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is  </strong> A)1200. B)1220. C)1222. D)1225. <div style=padding-top: 35px>

A)1200.
B)1220.
C)1222.
D)1225.
سؤال
Given the demand and forecast values shown in the table below:
<strong>Given the demand and forecast values shown in the table below:   The forecast error for September is</strong> A)10.00. B)-10.00. C)1.00. D)39.00. <div style=padding-top: 35px>
The forecast error for September is

A)10.00.
B)-10.00.
C)1.00.
D)39.00.
سؤال
Correlation is a measure of the strength of the

A)nonlinear relationship between two dependent variables.
B)nonlinear relationship between a dependent and independent variable.
C)linear relationship between two dependent variables.
D)linear relationship between a dependent and independent variable.
سؤال
Which of the following can be used to monitor a forecast to see if it is biased high or low?

A)a tracking signal
B)the mean absolute deviation (MAD)
C)the mean absolute percentage deviation (MAPD)
D)a linear trend line model
سؤال
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   The mean absolute deviation (MAD)for the end of May is</strong> A)7.0. B)7.5. C)10.0 D)3.0 <div style=padding-top: 35px>
The mean absolute deviation (MAD)for the end of May is

A)7.0.
B)7.5.
C)10.0
D)3.0
سؤال
A large positive cumulative error indicates that the forecast is probably

A)higher than the actual demand.
B)lower than the actual demand.
C)unbiased.
D)biased.
سؤال
If forecast errors are normally distributed then

A)1 MAD = 1σ
B)1 MAD ≈ 0.8 σ
C)0.8 MAD ≈ 1σ
D)1 MAD ≈ 1.96 σ
سؤال
Given the demand and forecast values below,the naïve forecast for September is
<strong>Given the demand and forecast values below,the naïve forecast for September is  </strong> A)100.6. B)99.0. C)102.0. D)cannot be determined. <div style=padding-top: 35px>

A)100.6.
B)99.0.
C)102.0.
D)cannot be determined.
سؤال
Given the demand and forecast values shown in the table below:
<strong>Given the demand and forecast values shown in the table below:   The three-period moving average forecast for November is</strong> A)516. B)528. C)524. D)515. <div style=padding-top: 35px>
The three-period moving average forecast for November is

A)516.
B)528.
C)524.
D)515.
سؤال
For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.30 is
<strong>For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.30 is  </strong> A)489. B)486. C)483. D)480. <div style=padding-top: 35px>

A)489.
B)486.
C)483.
D)480.
سؤال
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   At the end of May the tracking signal would be</strong> A)0.000. B)0.667. C)1.333. D)2.143. <div style=padding-top: 35px>
At the end of May the tracking signal would be

A)0.000.
B)0.667.
C)1.333.
D)2.143.
سؤال
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   The forecast error for February is</strong> A)10. B)-10. C)-15. D)-5 <div style=padding-top: 35px>
The forecast error for February is

A)10.
B)-10.
C)-15.
D)-5
سؤال
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   At the end of May the average error would be</strong> A)7. B)5. C)3. D)1. <div style=padding-top: 35px>
At the end of May the average error would be

A)7.
B)5.
C)3.
D)1.
سؤال
If the forecast for July was 3300 and the actual demand for July was 3250,then the exponential smoothing forecast for August using α = 0.20 is

A)3300.
B)3290.
C)3275.
D)3250.
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ملء الشاشة (f)
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Deck 12: Forecasting
1
Forecasting customer demand is rarely a key to providing good quality service.
False
2
A correlation coefficient is a measure of the strength of the linear relationship between an independent and a dependent variable.
True
3
The most common type of forecasting method for long-term strategic planning is based on quantitative modeling
False
4
A linear regression model that relates demand to time is known as a linear trend line.
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5
Forecast bias is measured by the per-period average of the sum of the forecast errors.
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6
One reason time series methods are popular for forecasting is that they are relatively easy to use and understand.
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7
The larger the mean absolute deviation (MAD)the more accurate the forecast.
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8
A gradual,long-term up or down movement of demand is referred to as a trend.
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9
The Delphi method generates forecasts based on informed judgments and opinions from knowledgeable individuals.
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10
Time series methods use historical data to predict future demand.
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11
The average,absolute difference between the forecast and demand is a popular measure of forecast error.
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12
The type of forecasting method used depends entirely whether the supply chain is continuous replenishment or not.
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13
Forecasts based on mathematical formulas are referred to as qualitative forecasts.
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14
Exponential smoothing is an averaging method for forecasting that reacts more strongly to recent changes in demand.
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15
A gradual,long-term up or down movement of demand is called a trend.
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16
Qualitative forecasts use mathematical techniques and statistical formulas.
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17
One way to deal with the bullwhip effect is to develop and share the forecasts with other supply chain members.
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18
Linear regression relates two variables using a linear model.
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19
Continuous replenishment systems rely heavily on extremely accurate long-term forecasts.
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20
A seasonal pattern is an oscillating movement in demand that occurs periodically over the short-run and is repetitive.
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21
Correlation in linear regression is a measure of the strength of the relationship between the dependent variable,demand,and an independent (explanatory)variable.
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22
The demand behavior for skis is considered cyclical.
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23
Movements in demand that do not follow a given pattern are referred to as random variations.
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24
The trend toward continuous replenishment in supply chain design has shifted the need for accurate forecasts from short-term to long-term.
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25
Because of advances in technology,many service industries no longer require accurate forecasts to provide high quality service.
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26
The type of forecasting method selected depends on time frame,demand behavior and causes of behavior.
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27
Because of ease of use and simplicity,exponential smoothing is preferred over smoothing average.
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28
Because of the development of advanced forecasting models managers no longer track forecast error.
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29
Long-range qualitative forecasts are used to determine future demand for new products,markets and customers.
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30
The moving average method is used for creating forecasts when there is no variation in demand.
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31
Sharing demand forecasts with supply chain members has resulted in an increased bullwhip effect.
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32
Short-midrange forecasts tend to use quantitative models that forecast demand based on historical demand.
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33
In today competitive environment,effective supply chain management requires accurate demand forecasts.
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34
Regression is used for forecasting when there is a relationship between the dependent variable,demand,and one or more independent (explanatory)variables.
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35
The long-term strategic planning process is dependent upon qualitative forecasting methods.
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36
Because of globalization of markets,managers are finding it increasingly more difficult to create accurate demand forecasts.
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37
Because of the heightened competition resulting from globalization most companies find little strategic value in long-range forecast.
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38
Time series methods assume that demand patterns in the past is a good predictor of demand in the future.
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39
Many companies are shifting from long-term to short-term forecast for strategic planning.
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40
Multiple regression analysis can be used to relate demand to two or more dependent variables.
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41
A long-range forecast would normally not be used to

A)design the supply chain.
B)implement strategic programs.
C)determine production schedules.
D)plan new products for changing markets
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42
A ___________ is an up-and-down movement in demand that repeats itself over a lengthy time period of more than a year.

A)trend
B)seasonal pattern
C)random variation
D)cycle
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43
An exponential smoothing forecasting technique requires all of the following except

A)the forecast for the current period.
B)the actual demand for the current period.
C)a smoothing constant.
D)large amounts of historical demand data.
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44
The weighted moving average forecast for the fifth period with weights of 0.15 for period 1,0.20 for period 2,0.25 for period 3,and 0.40 for period 4,using the demand data shown below is
<strong>The weighted moving average forecast for the fifth period with weights of 0.15 for period 1,0.20 for period 2,0.25 for period 3,and 0.40 for period 4,using the demand data shown below is  </strong> A)3760 B)3700 C)3650 D)3325

A)3760
B)3700
C)3650
D)3325
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45
The _________________ forecast method consists of an exponentially smoothed forecast with a trend adjustment factor added to it.

A)Exponentially smoothed
B)Adjusted exponentially smoothed
C)Time series
D)Moving average
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46
The per period average of cumulative error is called

A)cumulative forecast variation.
B)absolute error.
C)average error.
D)noise.
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47
The sum of the weights in a weighted moving average forecast

A)must equal the number of periods being averaged.
B)must equal 1.00.
C)must be less than 1.00.
D)must be greater than 1.00.
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48
Which of the following is not a type of predictable demand behavior?

A)trend
B)random variation
C)cycle
D)seasonal pattern
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49
The smoothing constant,α,in the exponential smoothing forecast

A)must always be a value greater than 1.0.
B)must always be a value less than 0.10.
C)must be a value between 0.0 and 1.0.
D)should be equal to the time frame for the forecast.
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50
Given the following demand data for the past five months,the three period moving average forecast for June is
<strong>Given the following demand data for the past five months,the three period moving average forecast for June is  </strong> A)103.33. B)99.00. C)95.00. D)92.50

A)103.33.
B)99.00.
C)95.00.
D)92.50
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51
The closer the smoothing constant,α,is to 1.0

A)the greater the reaction to the most recent demand.
B)the greater the dampening,or smoothing,effect.
C)the more accurate the forecast.
D)the less accurate the forecast.
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52
Regression forecasting methods relate _________to other factors that cause demand behavior.

A)Supply
B)Demand
C)Time
D)Money
E)Efficiency
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53
Selecting the type of forecasting method to use depends on

A)the time frame of the forecast.
B)the behavior of demand and demand patterns.
C)the causes of demand behavior.
D)all of the above.
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54
Forecast methods based on judgment,opinion,past experiences,or best guesses are known as ___________ methods.

A)quantitative
B)qualitative
C)time series
D)regression
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55
A qualitative procedure used to develop a consensus forecast is known as

A)exponential smoothing.
B)regression methods.
C)the Delphi technique.
D)naïve forecasting.
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56
Given the following demand data for the past five months,the four period moving average forecast for June is
<strong>Given the following demand data for the past five months,the four period moving average forecast for June is  </strong> A)96.25. B)99.00. C)110.00. D)93.75.

A)96.25.
B)99.00.
C)110.00.
D)93.75.
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57
The exponential smoothing model produces a naïve forecast when the smoothing constant,α,is equal to

A)0.00.
B)1.00.
C)0.50.
D)2.00
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58
A forecast where the current period's demand is used as the next period's forecast is known as a

A)moving average forecast.
B)naïve forecast.
C)weighted moving average forecast.
D)Delphi forecast.
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59
A company wants to product a weighted moving average forecast for April with the weights 0.40,0.35,and 0.25 assigned to March,February,and January,respectively.If the company had demands of 5,000 in January,4,750 in February,and 5,200 in March,then April's forecast is

A)4983.33.
B)4992.50.
C)4962.50.
D)5000.00.
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60
The _______ method uses demand in the first period to forecast demand in the next period.

A)naïve
B)moving average
C)exponential smoothing.
D)linear trend
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61
The mean absolute percentage deviation (MAPD)measures the absolute error as a percentage of

A)all errors.
B)per period demand.
C)total demand.
D)the average error.
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62
A tracking signal is computed by

A)multiplying the cumulative error by MAD
B)multiplying the absolute error by MAD
C)dividing MAD by the cumulative absolute error
D)dividing the cumulative error by MAD
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63
Which of the following is a reason why a forecast can go "out of control?"

A)a change in trend
B)an irregular variation such as unseasonable weather
C)a promotional campaign
D)all of the above
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64
A mathematical technique for forecasting that relates the dependent variable to an independent variable is

A)correlation analysis.
B)exponential smoothing.
C)linear regression.
D)weighted moving average.
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65
Given the demand and forecast values shown in the table below:
<strong>Given the demand and forecast values shown in the table below:   The exponential smoothing forecast for November using α = 0.35 is</strong> A)552.45. B)553.50. C)554.55. D)557.50.
The exponential smoothing forecast for November using α = 0.35 is

A)552.45.
B)553.50.
C)554.55.
D)557.50.
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66
Which of the following statements concerning average error is true?

A)a positive value indicates high bias,and a negative value indicates low bias
B)a positive value indicates zero bias,and a negative value indicates low bias
C)a negative value indicates zero bias,and a negative value indicates high bias
D)a positive value indicates low bias,and a negative value indicates high bias
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67
For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is
<strong>For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is  </strong> A)1200. B)1220. C)1222. D)1225.

A)1200.
B)1220.
C)1222.
D)1225.
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68
Given the demand and forecast values shown in the table below:
<strong>Given the demand and forecast values shown in the table below:   The forecast error for September is</strong> A)10.00. B)-10.00. C)1.00. D)39.00.
The forecast error for September is

A)10.00.
B)-10.00.
C)1.00.
D)39.00.
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69
Correlation is a measure of the strength of the

A)nonlinear relationship between two dependent variables.
B)nonlinear relationship between a dependent and independent variable.
C)linear relationship between two dependent variables.
D)linear relationship between a dependent and independent variable.
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70
Which of the following can be used to monitor a forecast to see if it is biased high or low?

A)a tracking signal
B)the mean absolute deviation (MAD)
C)the mean absolute percentage deviation (MAPD)
D)a linear trend line model
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71
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   The mean absolute deviation (MAD)for the end of May is</strong> A)7.0. B)7.5. C)10.0 D)3.0
The mean absolute deviation (MAD)for the end of May is

A)7.0.
B)7.5.
C)10.0
D)3.0
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72
A large positive cumulative error indicates that the forecast is probably

A)higher than the actual demand.
B)lower than the actual demand.
C)unbiased.
D)biased.
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73
If forecast errors are normally distributed then

A)1 MAD = 1σ
B)1 MAD ≈ 0.8 σ
C)0.8 MAD ≈ 1σ
D)1 MAD ≈ 1.96 σ
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74
Given the demand and forecast values below,the naïve forecast for September is
<strong>Given the demand and forecast values below,the naïve forecast for September is  </strong> A)100.6. B)99.0. C)102.0. D)cannot be determined.

A)100.6.
B)99.0.
C)102.0.
D)cannot be determined.
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75
Given the demand and forecast values shown in the table below:
<strong>Given the demand and forecast values shown in the table below:   The three-period moving average forecast for November is</strong> A)516. B)528. C)524. D)515.
The three-period moving average forecast for November is

A)516.
B)528.
C)524.
D)515.
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76
For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.30 is
<strong>For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.30 is  </strong> A)489. B)486. C)483. D)480.

A)489.
B)486.
C)483.
D)480.
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77
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   At the end of May the tracking signal would be</strong> A)0.000. B)0.667. C)1.333. D)2.143.
At the end of May the tracking signal would be

A)0.000.
B)0.667.
C)1.333.
D)2.143.
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78
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   The forecast error for February is</strong> A)10. B)-10. C)-15. D)-5
The forecast error for February is

A)10.
B)-10.
C)-15.
D)-5
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79
A forecasting model has produced the following forecasts:
<strong>A forecasting model has produced the following forecasts:   At the end of May the average error would be</strong> A)7. B)5. C)3. D)1.
At the end of May the average error would be

A)7.
B)5.
C)3.
D)1.
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80
If the forecast for July was 3300 and the actual demand for July was 3250,then the exponential smoothing forecast for August using α = 0.20 is

A)3300.
B)3290.
C)3275.
D)3250.
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