Presentation is loading. Please wait.

Presentation is loading. Please wait.

assignable variation Deviations with a specific cause or source.

Published byRafe Strickland Modified over 6 years ago

Similar presentations

Presentation on theme: "assignable variation Deviations with a specific cause or source."— Presentation transcript:

1 assignable variation Deviations with a specific cause or source.
forecast bias or assignable variation or MSE? assignable variation Deviations with a specific cause or source. Page 102 2nd Ed, Page 120 Click here for Hint

2 Black Swan An incident of extreme consequence, unexpected
Black Swan or naïve forecast or error? Black Swan An incident of extreme consequence, unexpected or considered highly improbable. Page 102 2nd Ed, Page 120 Click here for Hint

3 causal modeling Predicting an outcome by identifying its relationship
extrapolation or seasonality or causal modeling? causal modeling Predicting an outcome by identifying its relationship with one or other factors. Page 87 2nd Ed, Page 106 Click here for Hint

4 determination or regression analysis?
correlation coefficient or coefficient of determination or regression analysis? coefficient of determination Proportion of variation in a dependent variable that is explained by a regression model. Page 99 2nd Ed, Page 117 Click here for Hint

5 determination or regression analysis?
correlation coefficient or coefficient of determination or regression analysis? correlation coefficient A measure of the strength of any linear relationship between two sets of observations. Page 98 2nd Ed, Page 116 Click here for Hint

6 crowdsourcing Crowd outsourcing; combining independent
crowdsourcing or Delphi method or expert opinion panel? crowdsourcing Crowd outsourcing; combining independent efforts of many people to accomplish a task. Page 87 2nd Ed, Page 105 Click here for Hint

7 or time series decomposition?
exogenous variation or cyclic variation or time series decomposition? cyclic variation Seasonality with a cycle time longer than 1 year; generally associated with economic influences on time series data. Page 102 2nd Ed, Page 121 Click here for Hint

8 Or jury of executive opinion?
Delphi method or expert opinion panel Or jury of executive opinion? Delphi method A qualitative forecasting technique in which experts achieve consensus through a blind process via a facilitator. Page 87 2nd Ed, Page 105 Click here for Hint

9 dependent variable An outcome of interest influenced by one or more
seasonality or regression analysis or dependent variable? dependent variable An outcome of interest influenced by one or more factors. Page 87 2nd Ed, Page 106 Click here for Hint

10 error The difference between an observed value and a predicted value.
natural variation or forecasting or error? error The difference between an observed value and a predicted value. Page 90 2nd Ed, Page 108 Click here for Hint

11 exogenous variation A non-repeating deviation in a time series created
forecast bias or assignable variation or exogenous variation? exogenous variation A non-repeating deviation in a time series created by a distinct, identifiable external influence. Page 102 2nd Ed, Page 120 Click here for Hint

12 expert opinion panel A small group of highly knowledgeable people who
Delphi method or expert opinion panel Or jury of executive opinion? expert opinion panel A small group of highly knowledgeable people who develop prediction through discussion and consensus. Page 87 2nd Ed, Page 105 Click here for Hint

13 extrapolation or time series?
time series decomposition or extrapolation or time series? extrapolation Projecting existing data into the future. Page 88 2nd Ed, Page 106 Click here for Hint

14 forecasting Predicting future events. forecasting or time series or
regression analysis? forecasting Predicting future events. Page 86 2nd Ed, Page 104 Click here for Hint

15 forecast bias A tendency to create errors that are predominantly
error or trend or forecast bias? forecast bias A tendency to create errors that are predominantly positive or negative. Page 90 2nd Ed, Page 109 Click here for Hint

16 or simple exponential smoothing?
independent variable or regression analysis or simple exponential smoothing? independent variable A factor used to predict an outcome of interest. Page 87 2nd Ed, Page 106 Click here for Hint

17 Or jury of executive opinion?
Delphi method or expert opinion panel Or jury of executive opinion? jury of executive opinion An expert panel composed of managers. Page 87 2nd Ed, Page 105 Click here for Hint

18 known unknown A source of uncertainty known to a decision maker,
known unknown or unknown unknown or trend? known unknown A source of uncertainty known to a decision maker, usually evident in past experience or data. Page 102 2nd Ed, Page 120 Click here for Hint

19 mean absolute deviation (MAD) An average of the absolute
MAPE or MAD or ME? mean absolute deviation (MAD) An average of the absolute values of a set of forecast errors. Page 91 2nd Ed, Page 109 Click here for Hint

20 mean absolute percent error (MAPE) Average of the absolute
MAPE or percent error or MSE? mean absolute percent error (MAPE) Average of the absolute values of a set of percent errors. Page 92 2nd Ed, Page 110 Click here for Hint

21 mean error (ME) An average of forecast errors; useful for indicating
MAPE or MAD or ME? mean error (ME) An average of forecast errors; useful for indicating forecast bias. Page 90 2nd Ed, Page 108 Click here for Hint

22 mean squared error (MSE) An average of the squared
MSE or MAD or ME? mean squared error (MSE) An average of the squared values of a set of forecast errors. Page 91 2nd Ed, Page 109 Click here for Hint

23 naïve forecast Assuming a future value equals the most recent
time series or naïve forecast or trend? naïve forecast Assuming a future value equals the most recent actual value available. Page 90 2nd Ed, Page 108 Click here for Hint

24 natural variation The randomness inherent, in a process, also known as
exogenous variation or natural variation or error? natural variation The randomness inherent, in a process, also known as random variation. Page 102 2nd Ed, Page 120 Click here for Hint

25 percent error Forecast error divided by the corresponding actual
forecast bias or MAPE or percent error? percent error Forecast error divided by the corresponding actual value. Page 92 2nd Ed, Page 110 Click here for Hint

26 planning horizon The farthest point in the future considered in
planning horizon or known unknown or extrapolation? planning horizon The farthest point in the future considered in decision making. Page 88 2nd Ed, Page 107 Click here for Hint

27 determination or regression analysis?
correlation coefficient or coefficient of determination or regression analysis? regression analysis Using mathematical relationships between two or more variables to predict future values. Page 95 2nd Ed, Page 113 Click here for Hint

28 responsiveness The degree to which a technique modifies
tracking signal or forecast bias or responsiveness? responsiveness The degree to which a technique modifies forecasts to reflect recent changes in past data. Page 94 2nd Ed, Page 112 Click here for Hint

29 seasonal relatives A set of numerical values that describe a seasonal
time series or seasonal relatives or exogenous variation? seasonal relatives A set of numerical values that describe a seasonal pattern. Page 103 2nd Ed, Page 121 Click here for Hint

30 seasonality A repeating pattern.
seasonal relatives or seasonality or trend? seasonality A repeating pattern. Page 102 2nd Ed, Page 121 Click here for Hint

31 simple exponential smoothing?
regression analysis or time series or simple exponential smoothing? simple exponential smoothing Predicting a future value by combining the previous prediction and some portion of the error in that prediction. Page 110 2nd Ed, Page 129 Click here for Hint

32 simple moving average Predicts a value by averaging a fixed number
regression analysis or time series or simple moving average? simple moving average Predicts a value by averaging a fixed number of most-recent actual values. Page 108 2nd Ed, Page 127 Click here for Hint

33 time series Values observed in chronological order.
time series or seasonality or planning horizon? time series Values observed in chronological order. Page 88 2nd Ed, Page 106 Click here for Hint

34 or regression analysis?
time series decomposition or time series or regression analysis? time series decomposition Modeling observed values based on identifiable component influences. Page 88 2nd Ed, Page 107 Click here for Hint

35 tracking signal Ratio of the sum of a set of forecast errors over the
MAPE or weighted moving average or tracking signal? tracking signal Ratio of the sum of a set of forecast errors over the MAD of that forecast. Page 92 2nd Ed, Page 110 Click here for Hint

36 trend A sustained period of growth or decline.
known unknown or tracking signal or trend? trend A sustained period of growth or decline. Page 102 2nd Ed, Page 121 Click here for Hint

37 unknown unknown Uncertainty omitted from planning because the
known unknown or unknown unknown or error? unknown unknown Uncertainty omitted from planning because the decision maker is unaware of its presence. Page 102 2nd Ed, Page 121 Click here for Hint

38 simple exponential smoothing?
MAPE or weighted moving average or simple exponential smoothing? weighted moving average Predicts a value by calculating a weighted average of a fixed number of most-recent actual values. Page 108 2nd Ed, Page 127 Click here for Hint

Download ppt "assignable variation Deviations with a specific cause or source."

Similar presentations

Forecasting OPS 370.

Forecasting OPS 370.
© 1997 Prentice-Hall, Inc. S2 - 1 Principles of Operations Management Forecasting Chapter S2.

© 1997 Prentice-Hall, Inc. S2 - 1 Principles of Operations Management Forecasting Chapter S2.
Operations Management Forecasting Chapter 4

Operations Management Forecasting Chapter 4
Chapter 11: Forecasting Models

Chapter 11: Forecasting Models
T18-03 - 1 T18-03 Exponential Smoothing Forecast Purpose Allows the analyst to create and analyze the Exponential Smoothing Average forecast. The MAD.

T T18-03 Exponential Smoothing Forecast Purpose Allows the analyst to create and analyze the "Exponential Smoothing Average" forecast. The MAD.
Forecasting 5 June 2001. Introduction What: Forecasting Techniques Where: Determine Trends Why: Make better decisions.

Forecasting 5 June Introduction What: Forecasting Techniques Where: Determine Trends Why: Make better decisions.
Qualitative Forecasting Methods

Qualitative Forecasting Methods
Forecasting Ross L. Fink.

Forecasting Ross L. Fink.
Chapter 12 - Forecasting Forecasting is important in the business decision-making process in which a current choice or decision has future implications:

Chapter 12 - Forecasting Forecasting is important in the business decision-making process in which a current choice or decision has future implications:
Data Sources The most sophisticated forecasting model will fail if it is applied to unreliable data Data should be reliable and accurate Data should be.

Data Sources The most sophisticated forecasting model will fail if it is applied to unreliable data Data should be reliable and accurate Data should be.
Forecasting.

Forecasting.
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ 07458 PERTEMUAN 14.

To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 5-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ PERTEMUAN 14.
Chapter 13 Forecasting.

Chapter 13 Forecasting.
Operations Management R. Dan Reid & Nada R. Sanders

Operations Management R. Dan Reid & Nada R. Sanders
Operations Management Forecasting Chapter 4

Operations Management Forecasting Chapter 4
© 2004 by Prentice Hall, Inc., Upper Saddle River, N.J. 07458 4-1 Operations Management Forecasting Chapter 4.

© 2004 by Prentice Hall, Inc., Upper Saddle River, N.J Operations Management Forecasting Chapter 4.
4 Forecasting PowerPoint presentation to accompany Heizer and Render

4 Forecasting PowerPoint presentation to accompany Heizer and Render
Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Forecasting Operations Chapter 12 Roberta Russell & Bernard.

Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Forecasting Operations Chapter 12 Roberta Russell & Bernard.
Slides 13b: Time-Series Models; Measuring Forecast Error

Slides 13b: Time-Series Models; Measuring Forecast Error
LSS Black Belt Training Forecasting. Forecasting Models Forecasting Techniques Qualitative Models Delphi Method Jury of Executive Opinion Sales Force.

LSS Black Belt Training Forecasting. Forecasting Models Forecasting Techniques Qualitative Models Delphi Method Jury of Executive Opinion Sales Force.

Similar presentations

Ads by Google