Although you may not yet know what we mean by the term chemometrics, you almost certainly make routine use of chemometric techniques in your classes and labs: reporting an average result for several trials of an experiment or creating a calibration curve and using it to find an analyte’s concentration are two examples of chemometric methods analysis with which you almost certainly are familiar. The goal of this textbook is to provide an introduction to chemometrics suitable for the undergraduate chemistry curriculum at the junior or senior level; indeed, much of this textbook's content, including many of the examples and exercises, were developed to support Chem 351: Chemometrics, a course that has been part of the analytical curriculum at DePauw University since 2001 and that has been grounded in R since 2005.
Thumbnail: Cluster analysis with k-Means on a density-based data set. k-means tries to model the data using Voronoi cells, but there is no linear separation possible, and the result is not particular meaningful. The visualization was generated using ELKI. (CC BY-SA_NC; Chire via Wikipedia)