A statistical method utilizing principal component factor analysis (PCFA) was developed for chemical/sensory taste and odor correlation. With this method, specific flavor descriptors can be correlated with specific chromatographic peaks. A background odor mechanism was assumed to explain the odors perceived at or below their odor threshold concentrations. PCFA was applied to a series of simulated data sets and chemical/sensory data obtained from drinking water samples. The simulated data sets were used to evaluate six types of chemical/sensory response equations. The response equation giving satisfactory correlation results was then used to evaluate the drinking water sample data sets. After merger of the chemical/sensory data, the covariance between items was calculated, and PCFA was applied to the covariance structure followed by a target transformation of PCFA factors. Quality assurance evaluations of both sensory and chemical data were an integral part of the correlation procedure. The correlation study using simulated data showed that the PCFA correlation method using linear-additive (e.g., log-additive) data yielded better results (i.e., less type I and II errors) than nonlinear, nonadditive data. The quality of the drinking water sample correlation results was highly dependent on the sensory data quality.