# CONTINUATION forecasting chapter chp 3 exam 2 p301

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1. exponential smoothing
a weighted averaging method based on previous forecast plus a percentage of the forecast error. ( using less makes it more accurate)
2. the smaller the a (alpha) the more _______
stable
3. the larger the a (alpha) the more____
responsive
4. if your data has randomness and your data has trend these are good to use
double moving average and double exponential smoothing( trend adjusted exponential smoothing)
5. regression is good for measuring ______
trend
6. when you have randomness, trend, seasonality, and multi year data you would use
classical decomposition method or box Jenkins
7. seasonality
regularly repeating movements in series values that can be tried to recurring events
8. calculating seasonal indexes
9. if you have no seasonality the index number will be ____
1
10. cycles
are similar to seasonal variations but are of longer durations
11. Accuracy and Control
12. Components of a time series
• trends- tendency of a time series to move upwards or downwards over time
• cycle- the effect on a time series caused by economic cycles
• seasonal- short term regular variations in data caused by calendar related events
• irregular variations- unpredictable and unexplainable fluctuations normal unusal circumstance
13. Involves all the _____ and control activites associated with the transformation process of both goods and service
planning
14. types of forecasting
• Judgmental- uses subjective inputs
• Associative- uses explanatory variables to predict furture
• Quantitive- uses historical data assuming the future will be like the past
15. time series forecasts
forecasts the project patterns identified in recent time series observation
16. time series forecasts Navie forecasting
uses a single previous value of a time as the basis for a forecast
17. time series forecasting- Techniques
• Moving avrg
• weighted moving avrg
• Exponential smoothing
18. Moving Average
• technique that averages a number of most recent actual values in generating forecast
• As new data becomes available, the forecast is updated by adding new values and dropping the oldest
• fewer data points- more responsive
• more data points- less responsive
19. Weighted Moving Average
The most recent values in a time series are given more weight in computing forecasts
20. Exponentiation Smoothing
• the most recent observations might have the highest predictive value
• we should give more weight to the more recent time periods
• Alpha and Beta are smoothing constants
• has the ability to respond to changes in trends
• has to components; smoothing error, trend factor
22. Model of seasonality
• Additive- seasonality is expressed as quantity that gets added or subtracted
• Multiplicative-is expressed as a percentage of the average amount which is then used to multiply the value of a series
23. Seasonal relative
• the seasonal percentage used in the multiplicative seasonally adjusted forecasting model
• to deseasonalize data-done to get a clear picture of nonseasonal components of data series
• to incorporate seasonality in a forecast-
24. Techniques for Cycles
cycles are similar to seasonal variation but are of longer durations
25. Regression- a technique for fitting a line to a set of data points
26. Forecasted-Accuracy and control
• forecaster want to minimize forecast errors
• forecast accurarcy should be an important forecasting technique selection criterion
• Error=Actual- Foretasted
27. error
the difference between actual and predicted value
28. Operations Strategy
the better forecasts are , the more able companies will be to take advantage of future opportunities and reduce potential risks
29. two important aspects of forecasting
• level of demand
• accuracy
 Author: Cshowalter ID: 296203 Card Set: CONTINUATION forecasting chapter chp 3 exam 2 p301 Updated: 2015-03-03 23:16:27 Tags: p301 Folders: p301 Description: p301 Show Answers: