Beer's law is an ideal technique that works only in certain situations. A method for dealing with more complex conditions needs to be integrated into the analytical chemistry curriculum. For that reason, the capabilities and limitations of two common chemometric algorithms, classical least squares (CLS) and principal component regression (PCR), are explored and a method for introducing these techniques into an analytical chemistry curriculum is described. Students find that while both algorithms are a better approach to real-world situations than Beer's law, PCR is superior to CLS because fewer restrictions are imposed. In addition to learning the important role that chemometrics is able to play in analytical chemistry, students gain hands-on practice with sample preparation and experience with FTIR spectroscopic measurement techniques. Also, this exercise can be completed in one four hour laboratory period. (Contains 1 figure and 2 tables.)