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OMGT 3223 Final Exam-ECU Questions and Answers
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OMGT 3223 Final Exam-ECU Questions and Answers
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OMGT 3223 Final Exam-ECU Questionsand Answers
Quantitative Forecasts - Answer-Quantitative forecasts are usually the result of
conventional statistical analysis.
Used when situation is 'stable' and historical data exist.
Involve mathematical techniques.
Qualitative Forecasts - Answer-Qualitative forecasts are usually the result of experts'
judgments and opinions. Senior management, marketing,
purchasing, and engineering are usually sources for internal qualitative forecasts.
Used when the situation is 'vague' and little data exist.
Involve intuition and experience.
Delphi Method (Qualitative Forecasting technique) - Answer-Procedure for acquiring
informed judgments and opinions from knowledgeable individuals using a series of
questionnaires in order to develop a consensus forecast about what will occur in the
future.
Sales-force composite - Answer-Procedure for developing forecasts where
salespersons' estimates of expected sales are combined or added together.
Time Series (Quantitative Forecasting method) - Answer-Statistical techniques that use
historical demand data to predict future demand.
Regression Methods - Answer-Techniques that develop a mathematical relationship
between a variable and the different factors that cause its behavior.
Time Frame - Answer-planning horizon.. short, mid, long range forecasts
Short- to mid-range forecasts (Quant) - Answer-Usually encompass the immediate
future (Planning horizon: Daily up to a year)
Long-range forecasts (qual) - Answer-Usually encompass a period of time longer than a
year.
Trends - Answer-Gradual long-term up or down movements of demand.
Seasonal Patterns - Answer-Up-and-down repetitive movements in demand occurring
periodically (Typically occur within 1 year)
Cycles - Answer-Repeating up and down movements (Typically 2-10 years duration).
Simple Moving average - Answer-(Sum of the data)/Number of periods
, weighted moving average - Answer-(W*D)+(W2*D2)+...
exponential smoothing - Answer-Ft +1 = α Dt + (1 - α) Ft
where:
Ft +1 = forecast for next period
Dt = actual demand for present period
Ft = forecast for present period
α = weighting factor or smoothing constant
cumulative error - Answer-CE =sum(actual -forecaset)
where:
et = error for period t
Note:
A large positive CE value indicates forecasts are consistently smaller than actual
demand.
A large negative CE value implies forecasts are consistently larger than actual demand.
average error - Answer-The Average Error is referred to as the bias of the forecast.
Ideally, we would like the bias of a forecast to be zero.
(sum of et)/n
where:
et = error for period t
n = number of forecast periods
MSE - Answer-The MSE measures the average of the squared differences between the
forecasts and actual demand.
(sum (et^2))/n
where:
et = error for period t
n = number of forecast periods
RMSE - Answer-The RMSE is calculated by taking the square root of the MSE. The
RMSE is expressed the same unit of measurement
as the quantity being estimated.
RMSE=sqrt((sum (et^2))/n)
where:
et = error for period t
n = number of forecast periods
MAE - Answer-MAE measures the average of the absolute differences between the
forecasts and actual demand. MAE is a popular and simple to use measure of forecast
accuracy.
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