Deck 10: Managing Demand and Forecasting
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Deck 10: Managing Demand and Forecasting
1
One of the basic time series patterns is random.
True
2
So called cyclical patterns involving gradual increases or decreases in demand over long periods of time cannot be predicted with forecasting.
False
3
Doctors,dentists,lawyers,and automobile repair shops are examples of service providers that use appointment systems.
True
4
Judgment methods of forecasting are quantitative methods that use historical data on independent variables to predict demand.
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5
The repeated observations of demand for a product or service in their order of occurrence form a pattern known as a time series.
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6
Judgment methods of forecasting should never be used with quantitative forecasting methods.
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7
An independent variable is the measure or quantity being forecast in linear regression analysis.
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8
A backorder is a customer order that cannot be filled immediately but is filled as soon as possible.
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9
A backorder is the same as backlog.
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10
The Delphi method is a process of gaining consensus from a group of experts while maintaining their anonymity.
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11
Promotional campaigns are designed to increase sales with creative pricing.
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12
One of the basic time series patterns is trend.
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13
Random variation is an aspect of demand that increases the accuracy of the forecast.
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14
Executive opinion is a forecasting method in which the opinion,experience,and technical knowledge of one or more managers are summarized to arrive at a single forecast.
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15
Sales force estimates are extremely useful for technological forecasting.
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16
Time-series analysis is a statistical approach that relies heavily on historical demand data to project the future size of demand.
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17
Linear regression analysis always involves predicting one dependent variable based on one independent variable.
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18
Aggregation is the act of clustering several similar products or services.
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19
Aggregating products or services together generally decreases the forecast accuracy.
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20
A backlog is an accumulation of customer orders that a manufacturer has promised for delivery at some future date.
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21
The tracking signal is a measure that indicates whether a method of forecasting is accurately predicting actual change in demand.
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22
The process of developing a forecast based on gaining consensus from a group of experts while maintaining their anonymity is called the Delphi method.
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23
Aggregating the sales of several products (product family forecasts)provides less accurate forecasts for total sales than developing separate forecasts for each product and adding up to forecast values.
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24
A business firm can be provided with the expected level of demand for goods and services by an economic forecast.
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25
Forecast error is simply the difference between the forecast and actual demand.
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26
Forecasts always contain errors.
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27
When using linear regression for forecasting,the independent variable is the variable that one wants to forecast.
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28
Only a handful of organizations experience seasonal demand for their goods or services.
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29
In developing a regression equation of the form Y = a + bX,the intent is to use values of X to predict the likely outcome for the dependent variable Y.
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30
A seasonal demand time series has a repeatable of pattern increases or decreases in demand based on the week,month,or seasons of the year.
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31
In relation to forecasting,there are no natural laws that make the relationship between demand and other variables continue to behave as they have done in the past.
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32
Exponential smoothing is an expensive forecasting method.
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33
A naive forecast is a time-series method whereby the forecast for the next period equals the demand for the current period.
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34
Some analysts prefer to use a holdout set as the final test of a forecasting procedure.
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35
The exponential smoothing method is a sophisticated weighted moving average method.
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36
Combination forecasting is a method of forecasting that selects the best forecast from a group of forecasts generated by simple techniques.
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37
When a trend is present,exponential smoothing always will be below or above the actual demand.
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38
A systematic increase or decrease in the mean of a demand time series over time is referred to as a cyclical time series.
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39
There is an expectation that forecasting models do make errors.
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40
The advantage of the simple moving average forecast is that it allows you to emphasize recent demand over earlier demand.
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41
Forecasting analysts try to minimize the effects of biased and random errors when determining a forecasting method.
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42
A systematic increase or decrease in the mean of a demand time series is referred to as
A) random variation.
B) a seasonal pattern.
C) a cyclical adjustment.
D) a trend.
A) random variation.
B) a seasonal pattern.
C) a cyclical adjustment.
D) a trend.
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43
A trend in a time series is a systematic increase or decrease in the average of the series over time.
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44
A tracking signal can be set at a predetermined level to alert a manager that action needs to be taken to modify the forecasting model.
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45
An initial forecast must be obtained by another method,before beginning a series of exponentially smoothed forecasts.
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46
A quantitative approach is applied when using the Delphi forecasting method.
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47
Which one of the following statements about the patterns of a demand series is FALSE?
A) The five basic patterns of most business demand series are the horizontal, trend, seasonal, cyclical, and random.
B) Estimating cyclical movement is difficult. Forecasters do not know the duration of the cycle because they cannot predict the events that cause it.
C) The trend, over an extended period of time, always increases the average level of the series.
D) Every demand series has at least the following two components: horizontal and random.
A) The five basic patterns of most business demand series are the horizontal, trend, seasonal, cyclical, and random.
B) Estimating cyclical movement is difficult. Forecasters do not know the duration of the cycle because they cannot predict the events that cause it.
C) The trend, over an extended period of time, always increases the average level of the series.
D) Every demand series has at least the following two components: horizontal and random.
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48
There will be a lag behind the trend in actual demand when using single smooth forecasts.
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49
changes in the dependent variable must take place with sufficient lead time before the associated change in the independent variables,for causal model to be useful as a forecasting tool.
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50
The mean forecast error (MFE)will approach one,if there is no bias in the forecasting model.
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51
A causal model,time cannot be used as an independent variable.
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52
Forecasting capacity needs is not generally considered important for service operations due to not having inventory.
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53
Which one of the following statements about forecasting is FALSE?
A) To achieve the objective of developing a useful forecast from the information at hand, the forecaster must select the appropriate technique. This choice sometimes involves a trade-off between forecast accuracy and cost.
B) Three general types of forecasting techniques are used for demand forecasting: time series analysis, causal methods, and judgment methods.
C) Time series express the relationship between the factor to be forecast and related factors, such as promotional campaigns, economic conditions, and competitor actions.
D) A time series is a list of repeated observations of a phenomenon, such as demand, arranged in the order in which they actually occurred.
A) To achieve the objective of developing a useful forecast from the information at hand, the forecaster must select the appropriate technique. This choice sometimes involves a trade-off between forecast accuracy and cost.
B) Three general types of forecasting techniques are used for demand forecasting: time series analysis, causal methods, and judgment methods.
C) Time series express the relationship between the factor to be forecast and related factors, such as promotional campaigns, economic conditions, and competitor actions.
D) A time series is a list of repeated observations of a phenomenon, such as demand, arranged in the order in which they actually occurred.
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54
Which one of the following basic patterns of demand is difficult to predict because it is affected by national or international events or because of a lack of demand history reflecting the stages of demand from product development to decline?
A) horizontal
B) seasonal
C) random
D) cyclical
A) horizontal
B) seasonal
C) random
D) cyclical
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55
The stability of a moving average forecast is inversely related to the number of periods included in the moving average.
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56
The moving average gives a forecast of the mean value of demand in future periods,if there is no noticeable trend or seasonality in the data.
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57
Delphi forecasting refers to a change in the forces that have acted on demand in the past.
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58
Using sales force estimates for forecasting has the advantage that
A) no biases exist in the forecasts.
B) statistical estimates of seasonal factors are more precise than any other approach.
C) forecasts of individual sale force members can be easily combined to get regional or national sales totals.
D) confusion between customer "wants" (wish list) and customer "needs" (necessary purchases) is eliminated.
A) no biases exist in the forecasts.
B) statistical estimates of seasonal factors are more precise than any other approach.
C) forecasts of individual sale force members can be easily combined to get regional or national sales totals.
D) confusion between customer "wants" (wish list) and customer "needs" (necessary purchases) is eliminated.
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59
Forecasts will always be below or above the actual demand where a trend is present,unless exponential smoothing with two components is applied.
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60
Which one of the following statements about forecasting is TRUE?
A) The five basic patterns of demand are the horizontal, trend, seasonal, cyclical, and the subjective judgment of forecasters.
B) Judgment methods are designed particularly for situations when historical data are lacking.
C) Casual methods are used when historical data are available and the relationship between the factor to be forecast and other external and internal factors cannot be identified.
D) Focused forecasting is a technique that focuses on one particular component of demand and develops a forecast from it.
A) The five basic patterns of demand are the horizontal, trend, seasonal, cyclical, and the subjective judgment of forecasters.
B) Judgment methods are designed particularly for situations when historical data are lacking.
C) Casual methods are used when historical data are available and the relationship between the factor to be forecast and other external and internal factors cannot be identified.
D) Focused forecasting is a technique that focuses on one particular component of demand and develops a forecast from it.
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61
Which one of the following is an example of a time series forecasting technique?
A) survey analysis
B) Delphi method
C) trend-adjusted exponential smoothing
D) market research
A) survey analysis
B) Delphi method
C) trend-adjusted exponential smoothing
D) market research
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62
The Delphi method of forecasting is useful when
A) judgment and opinion are the only bases for making informed projections.
B) a systematic approach to creating and testing hypotheses is needed and the data are usually gathered by sending a questionnaire to consumers.
C) historical data are available and the relationship between the factor to be forecast and other external or internal factors can be identified.
D) historical data is available and the best basis for making projections is to use past demand patterns.
A) judgment and opinion are the only bases for making informed projections.
B) a systematic approach to creating and testing hypotheses is needed and the data are usually gathered by sending a questionnaire to consumers.
C) historical data are available and the relationship between the factor to be forecast and other external or internal factors can be identified.
D) historical data is available and the best basis for making projections is to use past demand patterns.
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63
Which one of the following time series forecasting methods will generate the most accurate forecasts when demands have a consistent trend pattern?
A) simple moving average method
B) weighted moving average method
C) exponential smoothing method
D) trend-adjusted exponential smoothing method
A) simple moving average method
B) weighted moving average method
C) exponential smoothing method
D) trend-adjusted exponential smoothing method
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64
Table 10.1
-Use the information in Table 10.1.What would be the forecast for September if the exponential smoothing technique were used? (? = 0.30 and the forecast for March was 55)
A) less than or equal to 65
B) greater than 65 but less than or equal to 67
C) greater than 67 but less than or equal to 69
D) greater than 69
-Use the information in Table 10.1.What would be the forecast for September if the exponential smoothing technique were used? (? = 0.30 and the forecast for March was 55)
A) less than or equal to 65
B) greater than 65 but less than or equal to 67
C) greater than 67 but less than or equal to 69
D) greater than 69
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65
Table 10.1
-Use the information in Table 10.1.Your boss has asked you to find a good technique to forecast short-term demand for an important product.You have decided to test the following four techniques against the historical data already given:
?Three-month simple moving average
?Three-month weighted moving average,with weight of 0.6 for the most recent month,0.3 for the second-most-recent month,and 0.1 for the third-most-recent month
?Three-month weighted moving average,with weights of 0.5 for the most recent month,0.3 for the second-most-recent month,and 0.2 for the third-most-recent month
HExponential smoothing (a = 0.3 and the forecast for March was 55)
Use each of the four techniques to forecast April through August,and then use the five months of forecasts to calculate MAD.Round all forecasts to the nearest whole number (i.e.,57.5 rounds to 58)just before doing your MAD calculations.Which of the four techniques is best in terms of MAD?
A) three-month simple moving average
B) three-month weighted moving average (0.6, 0.3, 0.1)
C) three-month weighted moving average (0.5, 0.3, 0.2)
D) exponential smoothing (a = 0.3)
-Use the information in Table 10.1.Your boss has asked you to find a good technique to forecast short-term demand for an important product.You have decided to test the following four techniques against the historical data already given:
?Three-month simple moving average
?Three-month weighted moving average,with weight of 0.6 for the most recent month,0.3 for the second-most-recent month,and 0.1 for the third-most-recent month
?Three-month weighted moving average,with weights of 0.5 for the most recent month,0.3 for the second-most-recent month,and 0.2 for the third-most-recent month
HExponential smoothing (a = 0.3 and the forecast for March was 55)
Use each of the four techniques to forecast April through August,and then use the five months of forecasts to calculate MAD.Round all forecasts to the nearest whole number (i.e.,57.5 rounds to 58)just before doing your MAD calculations.Which of the four techniques is best in terms of MAD?
A) three-month simple moving average
B) three-month weighted moving average (0.6, 0.3, 0.1)
C) three-month weighted moving average (0.5, 0.3, 0.2)
D) exponential smoothing (a = 0.3)
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66
The multiplicative seasonal method is most appropriate when the
A) seasonal influence is a constant regardless of the level of demand.
B) seasonal influence is erratic, changing in the timing of the peaks and valleys.
C) seasonal influence is dependent on the level of demand.
D) demand each period is a constant multiple of the demand in the previous period.
A) seasonal influence is a constant regardless of the level of demand.
B) seasonal influence is erratic, changing in the timing of the peaks and valleys.
C) seasonal influence is dependent on the level of demand.
D) demand each period is a constant multiple of the demand in the previous period.
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67
The judgment methods of forecasting are to be used for purposes of
A) making adjustments to quantitative forecasts due to unusual circumstances.
B) forecasting seasonal demands in lieu of time series approaches.
C) avoiding the calculations necessary for quantitative forecasts.
D) making forecasts more variable.
A) making adjustments to quantitative forecasts due to unusual circumstances.
B) forecasting seasonal demands in lieu of time series approaches.
C) avoiding the calculations necessary for quantitative forecasts.
D) making forecasts more variable.
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68
A tracking signal greater than zero and a mean absolute deviation greater than zero imply that the forecast has
A) no bias and no variability of forecast error.
B) a nonzero amount of bias and a nonzero amount of forecast error variability.
C) no bias and a nonzero amount of forecast error variability.
D) a nonzero amount of bias and no variability of forecast error.
A) no bias and no variability of forecast error.
B) a nonzero amount of bias and a nonzero amount of forecast error variability.
C) no bias and a nonzero amount of forecast error variability.
D) a nonzero amount of bias and no variability of forecast error.
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69
Which one of the following statements about forecasting is FALSE?
A) You should use the simple moving average method to estimate the mean demand of a time series that has a pronounced trend and seasonal influences.
B) The weighted moving average method allows forecasters to emphasize recent demand over earlier demand. The forecast will be more responsive to change in the underlying average of the demand series.
C) The most frequently used time series forecasting method is exponential smoothing because of its simplicity and the small amount of data needed to support it.
D) In exponential smoothing, higher alpha values place greater weight on recent demands in computing the average.
A) You should use the simple moving average method to estimate the mean demand of a time series that has a pronounced trend and seasonal influences.
B) The weighted moving average method allows forecasters to emphasize recent demand over earlier demand. The forecast will be more responsive to change in the underlying average of the demand series.
C) The most frequently used time series forecasting method is exponential smoothing because of its simplicity and the small amount of data needed to support it.
D) In exponential smoothing, higher alpha values place greater weight on recent demands in computing the average.
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70
Which one of the following statements is TRUE?
A) The ideal of zero bias and zero MAD can be accomplished by systematically searching for the best values of the smoothing constants.
B) Bias is always less than MAD.
C) For projections of more stable demand patterns without trends, seasonal influences, or cyclical influences, use larger values of n in the simple moving average approach.
D) Getting a single forecast of 500 units for the month of July is better than getting a forecast that there is a 95 percent chance that demand for July will be between 450 and 550 units.
A) The ideal of zero bias and zero MAD can be accomplished by systematically searching for the best values of the smoothing constants.
B) Bias is always less than MAD.
C) For projections of more stable demand patterns without trends, seasonal influences, or cyclical influences, use larger values of n in the simple moving average approach.
D) Getting a single forecast of 500 units for the month of July is better than getting a forecast that there is a 95 percent chance that demand for July will be between 450 and 550 units.
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71
When the underlying mean of a time series is very stable and there are no trend,cyclical,or seasonal influences,
A) a simple moving average forecast with n = 20 should outperform a simple moving average forecast with n = 3.
B) a simple moving average forecast with n = 3 should outperform a simple moving average forecast with n = 20.
C) a simple moving average forecast with n = 20 should perform about the same as a simple moving average forecast with n = 3.
D) an exponential smoothing forecast with alpha = 0.30 should outperform a exponential smoothing forecast with alpha = 0.01.
A) a simple moving average forecast with n = 20 should outperform a simple moving average forecast with n = 3.
B) a simple moving average forecast with n = 3 should outperform a simple moving average forecast with n = 20.
C) a simple moving average forecast with n = 20 should perform about the same as a simple moving average forecast with n = 3.
D) an exponential smoothing forecast with alpha = 0.30 should outperform a exponential smoothing forecast with alpha = 0.01.
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72
Assume that a time series forecast is generated for future demand,and subsequently it is observed that the forecast method did not accurately predict the actual demand.Specifically,the forecast errors were found to be:
Mean absolute percent error = 10%
Cumulative sum of forecast errors = 0%
Which one of the statements concerning this forecast is TRUE?
A) The forecast has no bias but has a positive standard deviation of errors.
B) The forecast has a positive bias and a standard deviation of errors equal to zero.
C) The forecast has no bias and has a standard deviation of errors equal to zero.
D) The forecast has a positive bias and a positive standard deviation of errors.
Mean absolute percent error = 10%
Cumulative sum of forecast errors = 0%
Which one of the statements concerning this forecast is TRUE?
A) The forecast has no bias but has a positive standard deviation of errors.
B) The forecast has a positive bias and a standard deviation of errors equal to zero.
C) The forecast has no bias and has a standard deviation of errors equal to zero.
D) The forecast has a positive bias and a positive standard deviation of errors.
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73
Which one of the following is an example of causal forecasting technique?
A) weighted moving average
B) linear regression
C) exponential smoothing
D) Delphi method
A) weighted moving average
B) linear regression
C) exponential smoothing
D) Delphi method
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74
With the trend-adjusted exponential smoothing method,
A) the forecast for the next period is simply the average computed this period.
B) an estimate of the trend is computed by taking the difference between the demand this period and the demand last period to avoid lengthy averaging calculations.
C) the only smoothing is done on the trend estimates using exponential smoothing.
D) the forecast can be adjusted to account for changes in the trend.
A) the forecast for the next period is simply the average computed this period.
B) an estimate of the trend is computed by taking the difference between the demand this period and the demand last period to avoid lengthy averaging calculations.
C) the only smoothing is done on the trend estimates using exponential smoothing.
D) the forecast can be adjusted to account for changes in the trend.
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75
When the underlying mean of a time series changes frequently but there is no trend,cyclical,or seasonal influence,
A) a simple moving average forecast with n = 20 should outperform a simple moving average forecast with n = 3.
B) a simple moving average forecast with n = 3 should outperform a simple moving average forecast with n = 20.
C) a simple moving average forecast with n = 20 should perform about the same as a simple moving average forecast with n = 3.
D) an exponential smoothing forecast with alpha = 0.01 should outperform a exponential smoothing forecast with alpha = 0.30.
A) a simple moving average forecast with n = 20 should outperform a simple moving average forecast with n = 3.
B) a simple moving average forecast with n = 3 should outperform a simple moving average forecast with n = 20.
C) a simple moving average forecast with n = 20 should perform about the same as a simple moving average forecast with n = 3.
D) an exponential smoothing forecast with alpha = 0.01 should outperform a exponential smoothing forecast with alpha = 0.30.
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76
A weighted moving average method that calculates the average of a time series by giving recent demands more weight than earlier methods is called
A) seasonally adjusted smoothing.
B) exponential smoothing.
C) multiplicative seasonal method.
D) cumulative tracking error.
A) seasonally adjusted smoothing.
B) exponential smoothing.
C) multiplicative seasonal method.
D) cumulative tracking error.
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77
With the multiplicative seasonal method of forecasting,
A) the times series cannot exhibit a trend.
B) seasonal factors are multiplied by an estimate of average demand to arrive at a seasonal forecast.
C) the seasonal amplitude is a constant, regardless of the magnitude of average demand.
D) there can only be four seasons in the time series data.
A) the times series cannot exhibit a trend.
B) seasonal factors are multiplied by an estimate of average demand to arrive at a seasonal forecast.
C) the seasonal amplitude is a constant, regardless of the magnitude of average demand.
D) there can only be four seasons in the time series data.
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78
Which one of the following is most useful for measuring the bias in a forecast?
A) cumulative sum of forecast errors
B) standard deviation of forecast errors
C) mean absolute deviation of forecast errors
D) percentage forecast error in period t
A) cumulative sum of forecast errors
B) standard deviation of forecast errors
C) mean absolute deviation of forecast errors
D) percentage forecast error in period t
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79
Which of the following is an example of a judgmental forecasting technique?
A) market research
B) multiplicative seasonal method
C) simple moving average
D) linear regression
A) market research
B) multiplicative seasonal method
C) simple moving average
D) linear regression
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80
Which one of the following statements about forecasting is FALSE?
A) The method for incorporating a trend in an exponentially smoothed forecast requires the estimation of three smoothing constants: one for the mean, one for the trend, and one for the error.
B) The cumulative sum of forecast errors (CFE) is useful in measuring the bias in a forecast.
C) The standard deviation and the mean absolute deviation measure the dispersion of forecast errors.
D) A tracking signal is a measure that indicates whether a method of forecasting has any built-in biases over a period of time.
A) The method for incorporating a trend in an exponentially smoothed forecast requires the estimation of three smoothing constants: one for the mean, one for the trend, and one for the error.
B) The cumulative sum of forecast errors (CFE) is useful in measuring the bias in a forecast.
C) The standard deviation and the mean absolute deviation measure the dispersion of forecast errors.
D) A tracking signal is a measure that indicates whether a method of forecasting has any built-in biases over a period of time.
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