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Multiplicative 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) constantly fluctuate over time
D) remain linear over time

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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)

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"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

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A linear trend can be ______.


A) positive
B) cyclical
C) irregular
D) random

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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

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The regression sum of squares (SSR) is the ______.


A) unexplained variation
B) explained variation
C) total variation
D) random variation

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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

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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

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Which of the following methods is used by companies for monitoring and controlling forecasts?


A) tracking signals
B) trend charts
C) seasonal indices
D) control signals

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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.  Week  Number of Patients 11002803904100\begin{array} { | c | c | } \hline \text { Week } & \text { Number of Patients } \\\hline 1 & 100 \\\hline 2 & 80 \\\hline 3 & 90 \\\hline 4 & 100 \\\hline\end{array}


A) 93
B) 96
C) 98
D) 100

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______ 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

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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

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______ 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

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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

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Which of the following statements is false about tracking signals?


A) They monitor whether the forecasts lie around the target.
B) Both actual and forecasted demand values are required to calculate tracking signals.
C) They cannot be used to determine whether or not the demand pattern has changed.
D) They monitor whether the forecasts are consistently too high or low.

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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.

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______ 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

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With forecasting error being measured in MAD (mean absolute deviation) ,the 3σ control limits imply ______.


A) the probability that the forecasting errors are attributable to random variation is 3%
B) the probability that the forecasting errors are attributable to random variation is 99.7%
C) the probability that the forecasting errors are attributable to random variation is 2.3%
D) the probability that the forecasting errors are attributable to random variation is 50%

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Which of the following is NOT a step in supply chain forecasting for a company in the consumer products industry?


A) Determine the purpose of the forecast.
B) Collect non-historical data.
C) Adjust the baseline forecast for marketing promotions.
D) Share the forecast information with suppliers and downstream customers.

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______ are periodic,fairly short-term fluctuations in demand often caused by human activities or weather.


A) Cyclical variations
B) Seasonal variations
C) Irregular variations
D) Random variations

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