StatisticSpelled outCalculated for each.. LeverageObs DSSDimensionless SSObs and parameter CSSComposite SSParameter PCCParam. Cor. Coef.Parameter pair.

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Presentation transcript:

StatisticSpelled outCalculated for each.. LeverageObs DSSDimensionless SSObs and parameter CSSComposite SSParameter PCCParam. Cor. Coef.Parameter pair Cook’s DObs DFBETASObs and parameter PSSPrediction SSPred and parameter PPRParameter-PRedParameter OPRObs-PRedObs Review for Sensitivity Analysis Quiz SS Scaled Sensitivity

Sensitivity Analysis Quiz! Which statistics address which relations?? Observations – Parameters - Predictions Leverage OPR DSS PPR PCC CSS PSS Cook’s D DFBETAS Observations Predictions After Hill and Tiedeman, 2007, p. 263

Review for model fit quiz BIC AIC s 2 s S(b) Graphical analysis

Review for Uncertainty Analysis Quiz

UCODE_2005 documentation, Appendix B, p

Common questions that can be addressed by the methods taught here How much and what model complexity can the observations support? Are any of the estimated parameter values dominated by a single observation? What model parameters are important to the things I need to predict? What data should be collected to improve the predictions? Which conceptual model of the system is likely to produce better predictions? How certain are the predictions?

The 14 Guidelines Organized common sense with new perspectives and statistics Oriented toward clearly stating and testing all assumptions Emphasize graphical displays that are –statistically valid –informative to decision makers We can do more with our data and models!!