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Given an actual demand this period of 67, a forecast for this period of 58, and an alpha of 0.3, what would the forecast for the next period be using exponential smoothing?


A) 55.3
B) 57.1
C) 58.9
D) 61.0
E) 60.7

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________ forecasts address the business cycle by predicting inflation rates, money supplies, housing starts, and other planning indicators.

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Given forecast errors of -1, 4, 4, and -3, what is the mean absolute deviation?


A) 1
B) 3
C) 4
D) 8
E) 12

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If two variables were perfectly correlated, what would the coefficient of correlation r equal?


A) 0
B) -1
C) 1
D) B or C
E) none of these

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Cycles and random variations are both components of time series.

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The smaller the absolute tracking signal, the better the forecast is performing.

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The quarterly sales for specific educational software over the past three years are given in the following table. Compute the four seasonal factors. The quarterly sales for specific educational software over the past three years are given in the following table. Compute the four seasonal factors.

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Distinguish between a weighted moving average model and an exponential smoothing model.

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Exponential smoothing is a weighted movi...

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The degree or strength of a relationship between two variables is shown by the:


A) alpha.
B) mean.
C) mean absolute deviation.
D) coefficient of correlation.
E) cumulative error.

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Taco Bell's custom employee scheduling practices are partly the result of using:


A) point-of-sale computers to track food sales in 15-minute intervals.
B) focus forecasting.
C) a six-day moving average forecasting technique.
D) multiple regression.
E) mean absolute percentage of error minimization.

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The fundamental difference between cycles and seasonality is the:


A) duration of the repeating patterns.
B) magnitude of the variation.
C) ability to attribute the pattern to a cause.
D) all of the these
E) none of the these

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If Brandon Edward were working to develop a forecast using a moving averages approach, but he noticed a detectable trend in the historical data, he should:


A) use weights to place more emphasis on recent data.
B) use weights to minimize the importance of the trend.
C) change to an associative multiple regression approach.
D) use a simple moving average.
E) change to a qualitative approach.

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The jury of executive opinion forecasting method formally solicits input from customers and potential customers.

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A fundamental distinction between trend projection and linear regression is that:


A) trend projection uses least squares while linear regression does not.
B) only linear regression can have a negative slope.
C) in trend projection the independent variable is time; in linear regression the independent variable need not be time, but can be any variable with explanatory power.
D) trend projection can be a function of several variables, while linear regression can only be a function of one variable.
E) trend projection uses two smoothing constants, not just one.

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One use of short-range forecasts is to determine:


A) planning for new products.
B) cash budgeting.
C) research and development plans.
D) facility location.
E) production levels.

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A(n) ________ forecast uses an average of the most recent periods of data to forecast the next period.

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moving ave...

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Which time-series model below assumes that demand in the next period will be equal to the most recent period's forecast?


A) naive approach
B) moving average approach
C) weighted moving average approach
D) exponential smoothing approach with α = 0
E) trend projection

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A skeptical manager asks what long-range forecasts can be used for. Give her three possible uses/purposes.

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Any three of: planning for new...

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What is the forecast for May based on a weighted moving average applied to the following past demand data and using the weights: 4, 3, 3 (largest weight is for most recent data)? What is the forecast for May based on a weighted moving average applied to the following past demand data and using the weights: 4, 3, 3 (largest weight is for most recent data)?

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3 × 42 + 3 × 47 + 4 ...

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The major components of a time series are all of the following EXCEPT:


A) seasonality.
B) inflation.
C) trend.
D) cycles.
E) random variations.

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