Two dimensional correlation analysis is a mathematical technique that is used to study changes in measured signals. As mostly spectroscopic signals are discussed, sometime also two dimensional correlation spectroscopy is used and refers to the same technique. In 2D correlation analysis, a sample is subjected to an external perturbation while all other parameters of the system are kept at the same value. This perturbation can be a systematic and controlled change in temperature, pressure, pH, chemical composition of the system, or even time after a catalyst was added to a chemical mixture. As a result of the controlled change (the perturbation), the system will undergo variations which are measured by a chemical or physical detection method. The measured signals or spectra will show systematic variations that are processed with 2D correlation analysis for interpretation. When one considers spectra that consist of few bands, it is quite obvious to determine which bands are subject to a changing intensity. Such a changing intensity can be caused for example by chemical reactions. However, the interpretation of the measured signal becomes more tricky when spectra are complex and bands are heavily overlapping. Two dimensional correlation analysis allows one to determine at which positions in such a measured signal there is a systematic change in a peak, either continuous rising or drop in intensity. 2D correlation analysis results in two complementary signals, which referred to as the 2D synchronous and 2D asynchronous spectrum. These signals allow amongst others 1. * to determine the events that are occurring at the same time (in phase) and those events that are occurring at different times (out of phase) 2. * to determine the sequence of spectral changes 3. * to identify various inter- and intramolecular interactions 4. * band assignments of reacting groups 5. * to detect correlations between spectra of different techniques, for example near infrared spectroscopy (NIR) and Raman spectroscopy (en)