# Supply Chain Management Study Set 2

Statistics

## Quiz 3 :Forecasting Looking for Operations Management Homework Help?

## Quiz 3 :Forecasting

Showing 1 - 20 of 94  Continual review and updating in light of new data is a forecasting technique called second-guessing.
Free
True False

False Cyclical influences on demand are often expressed graphically as a linear function that is either upward or downward sloping.
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True False

False Cyclical influences on demand may come from occurrences such as political elections, war, or economic conditions.
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True False

True Trend lines are usually the last things considered when developing a forecast.
True False Time series forecasting models make predictions about the future based on analysis of past data.
True False In the weighted moving average forecasting model the weights must add up to one times the number of data points.
True False In a forecasting model using simple exponential smoothing the data pattern should remain stationary.
True False In a forecasting model using simple moving average, the shorter the time span used for calculating the moving average, the closer the average follows volatile trends.
True False In the simple exponential smoothing forecasting model you need at least 30 observations to set the smoothing constant alpha.
True False Experience and trial and error are the simplest ways to choose weights for the weighted moving average forecasting model.
True False Bayesian analysis is the simplest way to choose weights for the weighted moving average forecasting model.
True False The weighted moving average forecasting model uses a weighting scheme to modify the effects of individual data points. This is its major advantage over the simple moving average model.
True False A central premise of exponential smoothing is that more recent data is less indicative of the future than data from the distant past.
True False The equation for exponential smoothing states that the new forecast is equal to the old forecast plus the error of the old forecast.
True False Exponential smoothing is always the best and most accurate of all forecasting models.
True False In exponential smoothing, it is desirable to use a higher smoothing constant when forecasting demand for a product experiencing high growth.
True False The value of the smoothing constant alpha in an exponential smoothing model is between 0 and 1.
True False Simple exponential smoothing lags changes in demand.
True False   