Tham khảo tài liệu 'business process improvement_16', kỹ thuật - công nghệ, điện - điện tử phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Validate the Fitted Model ENGINEERING STATISTICS HANDBOOK TOOLS 4 4IOỈ home SEARCH BACK NfJiFI 5. Process Improvement . Case Studies . Eddy Current Probe Sensitivity Case Study . Validate the Fitted Model Model In the Important Factors and Parsimonious Prediction section we came to the following model Vallda ton Y - The residual standard deviation for this model is . The next step is to validate the model. The primary method of model validation is graphical residual analysis that is through an assortment of plots of the differences between the observed data Y and the predicted value V from the model. For example the design point -1 -1 -1 has an observed data point from the Background and data section of Y while the predicted value from the above fitted model for this design point is Ỹ -l -l which leads to the residual . Table of Residuals If the model fits well V should be near Y for all 8 design points. Hence the 8 residuals should all be near zero. The 8 predicted values and residuals for the model with these data are X1 X2 X3 Observed Predicted Residual -1 -1 -1 1 -1 -1 -1 1 -1 1 1 -1 -1 -1 1 1 -1 1 -1 1 1 1 1 1 Residual What is the magnitude of the typical residual There are several ways to compute this but the Standard statistically optimal measure is the residual standard deviation Deviation with ri denoting the ith residual N 8 is the number of observations and P 3 is the number of fitted parameters. From the Yates table the residual standard deviation is . http div898 handbook pri section6 1 of 3 5 1 2006 10 31 50 AM . Validate the Fitted Model How Should Residuals Behave If the prediction equation is adequate the residuals from that .
