![]() The display of the results may take few seconds as there are many tables and charts because of the 96 dependent variables.Īfter the tables displaying the basic statistics and the correlations between all the selected variables (dependent variables are displayed in blue and quantitative explanatory variables in black), the results specific to the PLS regression are presented. Interpreting the results of a Partial Least Squares regression You only need to click on "Done" so that the charts are only displayed for the first two axes. The display of the results is stopped to allow you to select the axes for the maps. The extremely fast computations start when you click on OK. The Vectors option has been unchecked in order not to saturate the charts. Last, in the Charts tab, the Colored labels option has been activated in order to make the reading of the charts easier. In the Options tab of the dialog box, we fix the number of components at 4 in the Stop conditions. The name of the orange juices has also been selected as Observation labels. ![]() In the Quantitative variable(s) field, select the explanatory variables, that are in our case the physicochemical descriptors. The ratings are the "Ys" of the model as we want to explain the ratings given by the judges. In the Dependent variable(s) field, select with the mouse the ratings of the 96 judges. Once you have clicked the button, the Partial Least Squares regression dialog box is displayed. To activate the Partial Least Squares regression dialog box, start first XLSTAT, then select the XLSTAT / Modeling data / Partial Least Squares Regression function. Setting up a Partial Least Squares regression Partial Least Squares regression is going to allow us to obtain a simultaneous map of the judges, the descriptors, and the products, and then to analyze for some judges which descriptors are related to their preferences. Goal of the Partial Least Squares regression in this example The data used in this article correspond to 6 orange juices described by 16 physico-chemical descriptors and evaluated by 96 judges. This tutorial is based on data that have been extensively analyzed in. Dataset for running a Partial Least Squares regression You now have the full version of XLSTAT Perpetual v2019.2.2 (圆4) installed on your PC.This tutorial shows how to set up and interpret a Partial Least Squares regression in Excel using the XLSTAT software.Copy XLSTATCR1C.dll from the Crack folder into your installation directory, and replace the previous file.Run xlstat_2019.2.2.exe and install the software.If you don’t know how to extract, see this article. This might take from a few minutes to a few hours, depending on your download speed. Click on the download button(s) below and finish downloading the required files.How to Download and Install XLSTAT Perpetual v2019.2.2 Operating System: Windows 11, Windows 10, Windows 8.1, Windows 7. ![]() ![]() XLSTAT Perpetual v2019.2.2 System Requirements
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