We see that the pr1 parameters that correspond to the maximum speed of group "a" and group "b" are quite close. The next table provides details on the model parameters after adjustment for each group. In our case, the RMCE is 42.865 in the first group, and 86.893 in the second, which shows that the variability of the speed is better explained in the first group. The sum of squares of residuals (SSE) is the criterion used by XLSTAT to fit the model. A model that fits the data better than another will have a lower RMCE. The second table (below) gives the model fit coefficients, including the RMCE (root mean square of the error) which gives an idea of the quality of a model. The first table of results provides simple statistics on the selected data. Interpreting the results of a nonlinear regression The computations begin once you have clicked on the OK button. The user will then have the choice to enter his own derivatives, or to let them be estimated by XLSTAT. NB: XLSTAT also leaves the choice to the user to enter a function defined by himself. Here, select Fit a single model from the drop-down list and then choose the Michaelis-Menten function. In the Functions tab, XLSTAT offers a wide choice of predefined functions whose derivatives are directly taken into account.
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As we have selected the column titles, we have left the option Variable labels activated. The group variable is used to separate the data in two groups "a" and "b". In this tutorial, we want to explain the variability of the "Speed" by that of the concentration of substrate: "conc". The quantitative explanatory variable is the concentration of substrate: "conc". The Dependent variable (or variable to model, or response variable) is in our case the "Speed". The nonlinear regression dialog box pops up. Setting up a nonlinear regressionĪfter opening XLSTAT, select the XLSTAT / Modeling data / Nonlinear regression command. For this purpose we will use the Michaelis- Menten model. Our goal is to study the relationship between the substrate concentration of an enzyme and its maximum velocity in two different groups. Nonlinear regression is used to model complex phenomena which cannot be handled by the linear model.
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ARRAY XLSTAT HOW TO
This tutorial explains how to set up and interpret a nonlinear regression in Excel with XLSTAT.