Chemometric tools make it possible to handle complex data and extract useful information. Unfortunately, going from univariate to multivariate analysis does not imply that there are fewer pitfalls and potential problems in the data analysis. There are, in fact, many more! In this course, we will go through many of the problems that occur when analyzing and interpreting multivariate data. The examples will mainly focus on the use of PCA and PLS but most of the conclusions are generally applicable.
For this course it is assumed that participants are familiar with basic chemometric methods including Principal Components Analysis (PCA) and Partial Least Squares regression (PLS).
This course will be delivered via WebEx webinar on July 15 in one segment of three and a half hours, from 7:00am to 10:30am PDT, 16:00-19:30 CET. The course material is based on our popular Eigenvector University course. Can’t join us live? We’ll record the lecture and make it available to registrants after the event.
The course will include several follow-along examples. In order to take advantage of these, participants should equip their computers with current versions of our MATLAB based software PLS_Toolbox. Alternately participants can use our stand-alone Solo software (available for Windows, MacOS and Linux). Demo copies will work just fine (they are full-featured and last for 30 days). Users with Eigenvector accounts can download free demos. If you don’t have an account, start by creating one.