Engineering Statistics Handbook Episode 6 Part 1 potx

4.6.1.11 Work This Example Yourself Process Modeling 4.6 Case Studies in Process Modeling 4.6.1 Load Cell Calibration 4.6.1.11 Work This Example Yourself View Dataplot Macro for this Case Study This page allows you to repeat the analysis outlined in the case study description on the previous page using Dataplot, if you have downloaded and installed it Output from each analysis step below will be displayed in one or more of the Dataplot windows The four main windows are the Output window, the Graphics window, the Command History window and the Data Sheet window Across the top of the main windows there are menus for executing Dataplot commands Across the bottom is a command entry window where commands can be typed in Data Analysis Steps Results and Conclusions Click on the links below to start Dataplot and run this case study yourself Each step may use results from previous steps, so please be patient Wait until the software verifies that the current step is complete before clicking on the next step The links in this column will connect you with more detailed information about each analysis step from the case study description Get set up and started Read in the data You have read columns of numbers into Dataplot, variables Deflection and Load Fit and validate initial model Plot deflection vs load Based on the plot, a straight-line model should describe the data well Fit a straight-line model to the data The straight-line fit was carried out Before trying to interpret the numerical output, a graphical residual analysis Plot the predicted values The superposition of the predicted http://www.itl.nist.gov/div898/handbook/pmd/section6/pmd61b.htm (1 of 3) [5/1/2006 10:22:37 AM] 4.6.1.11 Work This Example Yourself from the model and the data on the same plot and observed values suggests the model is ok Plot the residuals vs load The residuals are not random, indicating that a straight line is not adequate Plot the residuals vs the predicted values This plot echos the information in the previous plot Make a 4-plot of the residuals All four plots indicate problems with the model Refer to the numerical output from the fit The large lack-of-fit F statistic (>214) confirms that the straightline model is inadequate Fit and validate refined model Refer to the plot of the residuals vs load The structure in the plot indicates a quadratic model would better describe the data Fit a quadratic model to the data The quadratic fit was carried out Remember to the graphical residual analysis before trying to interpret the numerical output Plot the predicted values from the model and the data on the same plot The superposition of the predicted and observed values again suggests the model is ok Plot the residuals vs load The residuals appear random, suggesting the quadratic model is ok Plot the residuals vs the predicted values Do a 4-plot of the residuals Refer to the numerical output from the fit The plot of the residuals vs the predicted values also suggests the quadratic model is ok None of these plots indicates a problem with the model The small lack-of-fit F statistic (