Deck 16: Demand Forecasting Methods
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Deck 16: Demand Forecasting Methods
1
14)______ is used to forecast demand for a new product or service that is similar to existing products.
A)Market research
B)The Delphi method
C)A historical life-cycle analogy
D)A sales force opinion
A)Market research
B)The Delphi method
C)A historical life-cycle analogy
D)A sales force opinion
C
2
1)Which of the following is an example of a forecasted activity in tactical decision making?
A)new product development
B)sales and production planning
C)production scheduling
D)worker assignments
A)new product development
B)sales and production planning
C)production scheduling
D)worker assignments
B
3
10)Which of the following is an example of a qualitative method?
A)Delphi method
B)moving average
C)weighted moving average
D)linear trend analysis
A)Delphi method
B)moving average
C)weighted moving average
D)linear trend analysis
A
4
20)Which of the following is NOT a major component of a time series?
A)seasonal variations
B)trend line
C)irregular variations
D)best-fit line
A)seasonal variations
B)trend line
C)irregular variations
D)best-fit line
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5
9)The two broad categories of forecasting methods are ______
A)dependent and independent
B)time series and causal
C)qualitative and quantitative
D)time series and regression analysis
A)dependent and independent
B)time series and causal
C)qualitative and quantitative
D)time series and regression analysis
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6
6)Which of the following statements is FALSE about good forecasts?
A)Short-term forecasts tend to be more accurate than long-term forecasts.
B)Aggregate forecasts for groups of products or services tend to be more accurate than forecasts for individual products.
C)The forecasts for dependent-demand items are more accurate than forecasts for independent-demand items.
D)Long-term forecasts tend to be more accurate than short-term forecasts.
A)Short-term forecasts tend to be more accurate than long-term forecasts.
B)Aggregate forecasts for groups of products or services tend to be more accurate than forecasts for individual products.
C)The forecasts for dependent-demand items are more accurate than forecasts for independent-demand items.
D)Long-term forecasts tend to be more accurate than short-term forecasts.
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7
13)______ is a qualitative method that attempts to eliminate or minimize the problem of bias in the opinion of a single expert by using a panel of experts to generate forecasts.
A)Expert opinion
B)Sales force opinion
C)Market research
D)The Delphi method
A)Expert opinion
B)Sales force opinion
C)Market research
D)The Delphi method
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8
19)Past behavior of demand is indicative of its future behavior,therefore past demand data can be used to construct demand forecasts.This statement is the underlying principle of the ______ method.
A)causal
B)market research
C)time series analysis
D)Delphi
A)causal
B)market research
C)time series analysis
D)Delphi
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9
18)The two subcategories of quantitative methods are ______.
A)time series analysis and causal methods
B)simple linear regression and multiple linear regression analysis
C)exponential smoothing and seasonality techniques
D)simple moving average and weighted moving average
A)time series analysis and causal methods
B)simple linear regression and multiple linear regression analysis
C)exponential smoothing and seasonality techniques
D)simple moving average and weighted moving average
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10
2)Product scheduling and worker assignments are examples of forecasted activities in ______ decision-making.
A)operational
B)tactical
C)strategic
D)functional
A)operational
B)tactical
C)strategic
D)functional
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11
15)One drawback of surveys is that they are ______.
A)time-consuming
B)inexpensive
C)necessary for a high response rate
D)efficient
A)time-consuming
B)inexpensive
C)necessary for a high response rate
D)efficient
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12
3)In order to be useful,demand forecasts should be ______.
A)consistent
B)complex
C)time-consuming
D)inaccurate
A)consistent
B)complex
C)time-consuming
D)inaccurate
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13
12)______ methods are used when no measurable,reliable,historic,or statistical data are available and are primarily based on intuition,judgment,or informed opinions of experts in the industry.
A)Market research
B)Qualitative
C)Quantitative
D)Causal
A)Market research
B)Qualitative
C)Quantitative
D)Causal
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14
17)Which of the following statements is true about quantitative methods?
A)They are appropriate for demand forecasting if there are causal relationships between explanatory variables.
B)They cannot be used for short or medium-to-intermediate timeframes.
C)They are used if measurable,historical data are not available.
D)They are inappropriate for demand forecasting if there are causal relationships between explanatory variables.
A)They are appropriate for demand forecasting if there are causal relationships between explanatory variables.
B)They cannot be used for short or medium-to-intermediate timeframes.
C)They are used if measurable,historical data are not available.
D)They are inappropriate for demand forecasting if there are causal relationships between explanatory variables.
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15
16)______ methods can be used if measurable,historical data are available,and there is evidence that past demand is indicative of the future demand.
A)Simulation analysis
B)Qualitative
C)Quantitative
D)Market research
A)Simulation analysis
B)Qualitative
C)Quantitative
D)Market research
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16
4)Which of the following statements is FALSE about good forecasts?
A)They should be easy to interpret so that users have confidence in the forecasts.
B)The costs of preparing the forecasts should outweigh its benefits.
C)Any deviations from actual demand should be small.
D)They should be available within a reasonable timeframe.
A)They should be easy to interpret so that users have confidence in the forecasts.
B)The costs of preparing the forecasts should outweigh its benefits.
C)Any deviations from actual demand should be small.
D)They should be available within a reasonable timeframe.
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17
5)Which of the following is NOT a feature of a good forecast?
A)timely
B)complex
C)efficient
D)consistent
A)timely
B)complex
C)efficient
D)consistent
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18
7)______ is a part or component of an end product whose demand depends on the demand for the end product.
A)Dependent demand item
B)Independent demand item
C)Variable demand item
D)Seasonal demand item
A)Dependent demand item
B)Independent demand item
C)Variable demand item
D)Seasonal demand item
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19
11)Exponential smoothing and weighted moving average are examples of ______.
A)causal methods
B)qualitative methods
C)time series analysis
D)simulation methods
A)causal methods
B)qualitative methods
C)time series analysis
D)simulation methods
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20
8)An end product is a(n)______ whose demand is unrelated to the demand of any other product or item.
A)dependent demand item
B)independent demand item
C)variable demand item
D)seasonal demand item
A)dependent demand item
B)independent demand item
C)variable demand item
D)seasonal demand item
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21
28)______ is a forecasting method in which it is assumed that the demand in the next period will be the same as it is in the current period.
A)Moving average
B)Naïve approach
C)Simple average
D)Sales force opinion
A)Moving average
B)Naïve approach
C)Simple average
D)Sales force opinion
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22
40)Simple exponential smoothing or the first-order smoothing model can be used when ______.
A)demand exhibits different types of trend patterns
B)demand is constant or level
C)demand exhibits both trend and seasonal patterns
D)demand is fluctuating
A)demand exhibits different types of trend patterns
B)demand is constant or level
C)demand exhibits both trend and seasonal patterns
D)demand is fluctuating
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23
38)Which of the following is a component of trend-adjusted forecast (TAF)?
A)leading indicators
B)seasonal indices
C)trend factors
D)tracking signals
A)leading indicators
B)seasonal indices
C)trend factors
D)tracking signals
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24
22)A ______ trend often occurs when new products are introduced.
A)linear
B)nonlinear
C)no trend (level demand)
D)damped
A)linear
B)nonlinear
C)no trend (level demand)
D)damped
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25
31)______ is a short-term time series forecasting method in which forecasters assign more weight to most recent values in the time series if they feel that these values reflect how the actual demand will behave in the near future.
A)Moving average
B)Linear trend multiplicative method
C)Weighted moving average
D)Linear regression technique
A)Moving average
B)Linear trend multiplicative method
C)Weighted moving average
D)Linear regression technique
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26
24)Increased retail sales in December and peak demand for snow shovels during winter are examples of ______
A)cyclical variations
B)seasonal variations
C)irregular variations
D)random variations
A)cyclical variations
B)seasonal variations
C)irregular variations
D)random variations
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27
34)New forecast = [(α *latest observation)+((1 - α)* old forecast)] is the formula for ______.
A)moving average
B)weighted moving average
C)exponential smoothing
D)factor rating method
A)moving average
B)weighted moving average
C)exponential smoothing
D)factor rating method
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28
37)In order to begin exponential smoothing,a forecaster needs ______.
A)seasonal indices
B)tracking signals
C)the value of α
D)leading indicators
A)seasonal indices
B)tracking signals
C)the value of α
D)leading indicators
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29
26)______ variations are treated as outliers and are eliminated from consideration for forecasting purposes.
A)Cyclical
B)Seasonal
C)Irregular
D)Regular
A)Cyclical
B)Seasonal
C)Irregular
D)Regular
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30
32)Using the weighted average method,with W₁ = 0.5,W2 = 0.3 and W₃ = 0.2,compute the forecast for Week 5 with the data that follows. 
A)93
B)96
C)98
D)100

A)93
B)96
C)98
D)100
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31
21)Which of the following is a type of nonlinear trend pattern?
A)damped trend
B)trend line
C)no trend (level demand)
D)exponential growth
A)damped trend
B)trend line
C)no trend (level demand)
D)exponential growth
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32
30)Using the moving average technique,compute the forecast for Week 5 with n = 3 with the data that follows. 
A)100
B)90
C)80
D)75

A)100
B)90
C)80
D)75
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33
35)When the smoothing constant (α)is set to 1,then exponential smoothing is equivalent to ______.
A)naïve approach
B)weighted moving average
C)moving average
D)factor rating method
A)naïve approach
B)weighted moving average
C)moving average
D)factor rating method
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34
36)The smoothing constant can take a value between ______.
A)-1 to +1
B)0 to 1
C)-1 to 0
D)-∞ to +∞
A)-1 to +1
B)0 to 1
C)-1 to 0
D)-∞ to +∞
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35
27)Which of the following is NOT an example of short-term time series forecasting methods?
A)naïve approach
B)moving averages
C)exponential smoothing
D)expert opinion
A)naïve approach
B)moving averages
C)exponential smoothing
D)expert opinion
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36
39)Which of the following is FALSE about exponential smoothing models?
A)They create accurate forecasts.
B)They lend themselves to large-scale forecasting.
C)They are not very adaptive.
D)They can be easily applied and automated.
A)They create accurate forecasts.
B)They lend themselves to large-scale forecasting.
C)They are not very adaptive.
D)They can be easily applied and automated.
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37
23)A linear trend can be ______.
A)positive
B)cyclical
C)irregular
D)random
A)positive
B)cyclical
C)irregular
D)random
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38
29)______ is a short-term time series forecasting method in which the average of the most recent demand periods is used to predict demand in the future period.
A)Moving average
B)Naïve approach
C)Linear regression
D)Exponential smoothing
A)Moving average
B)Naïve approach
C)Linear regression
D)Exponential smoothing
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39
25)______ are wave-like oscillations in demand about the trend line caused by changes in economic or business cycles or due to changes in political conditions.
A)Cyclical variations
B)Seasonal variations
C)Irregular variations
D)Random variations
A)Cyclical variations
B)Seasonal variations
C)Irregular variations
D)Random variations
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40
33)Using the naïve approach,compute the forecast for Week 5 with the data that follows. 
A)90
B)80
C)110
D)100

A)90
B)80
C)110
D)100
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41
44)The line of best fit obtained by the least-squares method is called ______.
A)regression line
B)linear line
C)nonlinear line
D)moving average line
A)regression line
B)linear line
C)nonlinear line
D)moving average line
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42
41)Which of the following models can be used when demand exhibits different types of changing trend patterns?
A)simple exponential smoothing
B)second-order or double smoothing
C)third-order or triple smoothing
D)linear trend multiplicative method
A)simple exponential smoothing
B)second-order or double smoothing
C)third-order or triple smoothing
D)linear trend multiplicative method
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43
56)In linear regression analysis,the term predicted variable is another name for ______.
A)independent variable
B)random variable
C)dependent variable
D)discrete variable
A)independent variable
B)random variable
C)dependent variable
D)discrete variable
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44
54)Which of the following is a form of quantitative analysis that uses causal techniques in order to identify related variables in order to make forecasts?
A)associative methods
B)time series analysis
C)the Delphi method
D)moving average
A)associative methods
B)time series analysis
C)the Delphi method
D)moving average
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45
57)Which of the following is NOT used to evaluate the validity of the regression equation for forecasting?
A)standard error of the estimate
B)coefficient of determination
C)correlation coefficient
D)mean absolute deviation (MAD)
A)standard error of the estimate
B)coefficient of determination
C)correlation coefficient
D)mean absolute deviation (MAD)
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46
46)Which of the following is a model of combining the trend and seasonal components?
A)subtractive
B)multiplicative
C)trend-adjusted exponential smoothing
D)linear trend analysis
A)subtractive
B)multiplicative
C)trend-adjusted exponential smoothing
D)linear trend analysis
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47
50)Using the data that follows,compute the seasonal indices for January,February,and March using the simple average method. 
A)January: 0.10,February: 0.88,March: 0.92
B)January: 0.97,February: 1.01,March: 0.72
C)January: 0.87,February: 1.08,March: 0.92
D)January: 0.97,February: 0.88,March: 0.92

A)January: 0.10,February: 0.88,March: 0.92
B)January: 0.97,February: 1.01,March: 0.72
C)January: 0.87,February: 1.08,March: 0.92
D)January: 0.97,February: 0.88,March: 0.92
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48
59)The ______ is the proportion of variation explained by regression.
A)standard error of the estimate
B)total sum of squares (SST)
C)correlation coefficient
D)coefficient of determination
A)standard error of the estimate
B)total sum of squares (SST)
C)correlation coefficient
D)coefficient of determination
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49
51)In ______ method,the seasonal indices are expressed as percentage and the combined forecast is expressed as percentage adjustments of the underlying linear trend.
A)linear trend analysis
B)trend-adjusted exponential smoothing
C)linear trend multiplicative
D)linear trend additive
A)linear trend analysis
B)trend-adjusted exponential smoothing
C)linear trend multiplicative
D)linear trend additive
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50
58)Which of the following is NOT a measure of variation that must be calculated prior to determining the value of coefficient of determination (R²)?
A)total sum of squares (SST)
B)error sum of squares (SSE)
C)regression sum of squares (SSR)
D)cumulative sum of error (CSE)
A)total sum of squares (SST)
B)error sum of squares (SSE)
C)regression sum of squares (SSR)
D)cumulative sum of error (CSE)
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51
55)The independent variable in linear regression analysis is also referred to as the ______.
A)predicted variable
B)predictor variable
C)random variable
D)discrete variable
A)predicted variable
B)predictor variable
C)random variable
D)discrete variable
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52
60)In regression analysis,the ______ is the measure of the variation of the actual Y (independent variable)values around the mean Y (Y̅).
A)total sum of squares (SST)
B)error sum of squares (SSE)
C)regression sum of squares (SSR)
D)standard error of the estimate
A)total sum of squares (SST)
B)error sum of squares (SSE)
C)regression sum of squares (SSR)
D)standard error of the estimate
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53
42)______ is a predictive technique that models the relationship between a dependent variable and one or more independent variables.
A)Linear regression analysis
B)Linear trend multiplicative method
C)Linear trend additive method
D)Second-order or double smoothing
A)Linear regression analysis
B)Linear trend multiplicative method
C)Linear trend additive method
D)Second-order or double smoothing
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54
52)One requirement for using the linear trend multiplicative method is ______.
A)tracking signals should be used
B)time series demand data should exhibit a linear trend with seasonal variations
C)seasonal indices need not be available
D)time series demand should exhibit a nonlinear trend with seasonal variations
A)tracking signals should be used
B)time series demand data should exhibit a linear trend with seasonal variations
C)seasonal indices need not be available
D)time series demand should exhibit a nonlinear trend with seasonal variations
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55
49)Which of the following methods is used for calculating seasonal indices?
A)simple linear regression
B)centered moving average
C)multiple linear regression
D)weighted moving average
A)simple linear regression
B)centered moving average
C)multiple linear regression
D)weighted moving average
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56
48)Additive models are used when patterns of seasonal variations ______.
A)remain constant over time
B)become more or less pronounced as the trend component increases or decreases
C)keep fluctuating over time
D)exhibits different types of trend patterns
A)remain constant over time
B)become more or less pronounced as the trend component increases or decreases
C)keep fluctuating over time
D)exhibits different types of trend patterns
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57
53)Which of the following statements is true?
A)Leading indicators are frequently used to track cyclical fluctuations.
B)Leading indicators are frequently used to track seasonal fluctuations.
C)Lagging indicators are frequently used to track cyclical fluctuations.
D)Lagging indicators are frequently used to track seasonal fluctuations.
A)Leading indicators are frequently used to track cyclical fluctuations.
B)Leading indicators are frequently used to track seasonal fluctuations.
C)Lagging indicators are frequently used to track cyclical fluctuations.
D)Lagging indicators are frequently used to track seasonal fluctuations.
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58
45)Which of the following methods can be used to evaluate the trend component of a time series?
A)simple moving average
B)trend-adjusted exponential smoothing
C)simple linear regression
D)multiple linear regression
A)simple moving average
B)trend-adjusted exponential smoothing
C)simple linear regression
D)multiple linear regression
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59
43)______ method results in a straight line that minimizes the sum of the squares of the differences between the line and each of the actual observations.
A)Best-fit
B)Straight-line
C)Least-squares
D)Linear-line
A)Best-fit
B)Straight-line
C)Least-squares
D)Linear-line
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60
47)In a(n)______ model,the seasonal indices are added to the projected trend data to create a combined forecast.
A)additive
B)multiplicative
C)subtractive
D)trend-adjusted
A)additive
B)multiplicative
C)subtractive
D)trend-adjusted
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61
77)Which of the following is a drawback of mean absolute deviation (MAD)?
A)There is no information about the forecasting bias.
B)The cancellation of the positive and negative forecast errors can distort the information.
C)Large errors tend to be magnified because they are squared.
D)It is very complex to calculate.
A)There is no information about the forecasting bias.
B)The cancellation of the positive and negative forecast errors can distort the information.
C)Large errors tend to be magnified because they are squared.
D)It is very complex to calculate.
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62
80)Which of the following variations cannot be predicted and can be identified only after occurrence?
A)random variations
B)irregular variations
C)seasonal variations
D)cyclical variations
A)random variations
B)irregular variations
C)seasonal variations
D)cyclical variations
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63
62)Which of the following statements is true about the error sum of squares (SSE)?
A)It measures the variation resulting from the relationship between the independent and dependent variable.
B)It measures the variation of the actual Y (independent variable)values around the mean Y (Y̅).
C)It measures the variation not explained by the regression but resulting from other factors or variables.
D)It measures the variation explained by the regression.
A)It measures the variation resulting from the relationship between the independent and dependent variable.
B)It measures the variation of the actual Y (independent variable)values around the mean Y (Y̅).
C)It measures the variation not explained by the regression but resulting from other factors or variables.
D)It measures the variation explained by the regression.
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64
74)The tendency to consistently produce a particular type of forecast (high or low)that isn't accurate is called a(n)______.
A)overestimate
B)underestimate
C)bias
D)wrong estimate
A)overestimate
B)underestimate
C)bias
D)wrong estimate
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65
66)The correlation coefficient takes on a value between ______.
A)0 and 1
B)-1 and +1
C)-∞ to +∞
D)-2 to +2
A)0 and 1
B)-1 and +1
C)-∞ to +∞
D)-2 to +2
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66
76)Mean absolute percentage error (MAPE)is the ______.
A)average of the sum of the absolute differences between the actual and forecasted demand values
B)average of the sum of the squared differences between the actual and forecasted demand values
C)average of the absolute percentage error
D)average of the absolute differences between the actual and forecasted demand values
A)average of the sum of the absolute differences between the actual and forecasted demand values
B)average of the sum of the squared differences between the actual and forecasted demand values
C)average of the absolute percentage error
D)average of the absolute differences between the actual and forecasted demand values
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67
64)Which of the following statements is true about the coefficient of determination (R²)?
A)The higher the value of R²,the more confidence we have that the estimate is accurate.
B)The lower the value of R²,the more confidence we have that the estimate is accurate.
C)The value of R² has no significance on the accuracy of the estimate.
D)The estimate is accurate when R² = 0.
A)The higher the value of R²,the more confidence we have that the estimate is accurate.
B)The lower the value of R²,the more confidence we have that the estimate is accurate.
C)The value of R² has no significance on the accuracy of the estimate.
D)The estimate is accurate when R² = 0.
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68
65)The ______ measures the strength of the relationship between the independent and dependent variable in regression analysis.
A)standard error of the estimate
B)total sum of squares (SST)
C)coefficient of determination
D)correlation coefficient
A)standard error of the estimate
B)total sum of squares (SST)
C)coefficient of determination
D)correlation coefficient
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69
69)"The demand for a product is a function of both the price of the product and the dollars spent on promotions by the company that produced it." Which of the following methods is appropriate to forecast demand for the product?
A)simple linear regression analysis
B)multiple linear regression analysis
C)multiplicative method
D)additive method
A)simple linear regression analysis
B)multiple linear regression analysis
C)multiplicative method
D)additive method
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70
70)Which of following approaches should forecasters follow while choosing the best forecasting method?
A)Select the method that results in the fewest forecasting errors.
B)Examine the performance of a single forecasting method over time.
C)Select the method that results in the largest forecasting errors.
D)There is no significance on the forecasting method selected since there will always be differences between the forecasts and actual values.
A)Select the method that results in the fewest forecasting errors.
B)Examine the performance of a single forecasting method over time.
C)Select the method that results in the largest forecasting errors.
D)There is no significance on the forecasting method selected since there will always be differences between the forecasts and actual values.
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71
79)Which of the following statements is true about the forecasting error measures?
A)Mean absolute deviation is complex and difficult to compute.
B)Cumulative sum error tracks the forecasting bias.
C)Mean absolute deviation provides the percentage of error.
D)Mean squared errors cannot track the accuracy of the forecast.
A)Mean absolute deviation is complex and difficult to compute.
B)Cumulative sum error tracks the forecasting bias.
C)Mean absolute deviation provides the percentage of error.
D)Mean squared errors cannot track the accuracy of the forecast.
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72
63)The coefficient of determination has a value between ______.
A)0 and 1
B)-1 and +1
C)-∞ to +∞
D)-1 to 0
A)0 and 1
B)-1 and +1
C)-∞ to +∞
D)-1 to 0
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73
75)The ______ is the average of the sum of the squared differences between the actual and the forecasted demand values.
A)mean squared error (MSE)
B)mean absolute deviation (MAD)
C)mean absolute percentage error (MAPE)
D)cumulative sum error (CSE)
A)mean squared error (MSE)
B)mean absolute deviation (MAD)
C)mean absolute percentage error (MAPE)
D)cumulative sum error (CSE)
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74
67)The ______ measures the random variation,which is the variation of the actual (observed)y values from the predicted y values (ŷᵢ).
A)correlation coefficient
B)error sum of squares (SSE)
C)coefficient of determination
D)standard error of the estimate
A)correlation coefficient
B)error sum of squares (SSE)
C)coefficient of determination
D)standard error of the estimate
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75
71)Which of the following is NOT a way to measure forecasting errors?
A)mean squared error (MSE)
B)mean absolute deviation (MAD)
C)mean absolute percentage error (MAPE)
D)error sum of squares (SSE)
A)mean squared error (MSE)
B)mean absolute deviation (MAD)
C)mean absolute percentage error (MAPE)
D)error sum of squares (SSE)
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76
61)The regression sum of squares (SSR)is the ______.
A)unexplained variation
B)explained variation
C)total variation
D)random variation
A)unexplained variation
B)explained variation
C)total variation
D)random variation
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77
72)______ is the average of the sum of the absolute differences between the actual and forecasted demand values.
A)Mean squared error (MSE)
B)Mean absolute deviation (MAD)
C)Mean absolute percentage error (MAPE)
D)Cumulative sum error (CSE)
A)Mean squared error (MSE)
B)Mean absolute deviation (MAD)
C)Mean absolute percentage error (MAPE)
D)Cumulative sum error (CSE)
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78
68)Which of following assumptions related to the validity of the linear regression model is false?
A)The independent and dependent variables have a linear relationship.
B)The error terms have a constant variance.
C)The error terms are not normally distributed.
D)The error terms have no correlation.
A)The independent and dependent variables have a linear relationship.
B)The error terms have a constant variance.
C)The error terms are not normally distributed.
D)The error terms have no correlation.
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79
73)A large positive value of cumulative sum error (CSE)implies ______.
A)the forecast is consistently overstating the actual demand
B)the forecast is consistently understating the actual demand
C)the forecast is exactly equal to the actual demand
D)the forecast is never equal to actual demand
A)the forecast is consistently overstating the actual demand
B)the forecast is consistently understating the actual demand
C)the forecast is exactly equal to the actual demand
D)the forecast is never equal to actual demand
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80
78)"Cancellation of the positive and negative forecast errors can distort the information." This is a drawback of ______.
A)mean squared error (MSE)
B)mean absolute deviation (MAD)
C)mean absolute percentage error (MAPE)
D)cumulative sum error (CSE)
A)mean squared error (MSE)
B)mean absolute deviation (MAD)
C)mean absolute percentage error (MAPE)
D)cumulative sum error (CSE)
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