Statistics Toolbox

Part 1

Begin the demo by using the sliders in the Reaction Simulator window to control the partial pressures of three reactants: Hydrogen, n-Pentane, and Isopentane. Each time you click the Run button, the levels for the reactants and results of the run are entered in the Trial and Error Data window.

Based on the results of previous runs, you can change the levels of the reactants to increase the reaction rate. (The results are determined using an underlying model that takes into account the noise in the process, so even if you keep all of the levels the same, the results will vary from run to run.) You are allotted a budget of 13 runs. When you have completed the runs, you can use the Plot menu on the Trial and Error Data window to plot the relationships between the reactants and the reaction rate, or click the Analyze button. When you click Analyze, rsmdemo calls the rstool function, which you can then use to try to optimize the results.)

Next, perform another set of 13 runs, this time from a designed experiment. In the Experimental Design Data window, click the Do Experiment button. rsmdemo calls the cordexch function to generate a D-optimal design, and then, for each run, computes the reaction rate.

Now use the Plot menu on the Experimental Design Data window to plot the relationships between the levels of the reactants and the reaction rate, or click the Response Surface button to call rstool to find the optimal levels of the reactants.

Compare the analysis results for the two sets of data. It is likely (though not certain) that you'll find some or all of these differences:

• You can fit a full quadratic model with the data from the designed experiment, but the trial and error data may be insufficient for fitting a quadratic model or interactions model.
• Using the data from the designed experiment, you are more likely to be able to find levels for the reactants that result in the maximum reaction rate. Even if you find the best settings using the trial and error data, the confidence bounds are likely to be wider than those from the designed experiment.

The rsmdemo Demo

Part 2