Evaluation of Analytical Data

Abstract

The study of food analysis involves a considerable amount of time learning principles, methods, and instrument operations and perfecting various techniques. These areas are extremely important, but much of our effort would be for naught if there were no ways to evaluate the data obtained from the various analytical assays. Having a good understanding of the data and how to interpret the data are critical to good decision making, whether in the food industry or in a research laboratory. This chapter focuses on statistical methods to evaluate the data obtained from analytical techniques. The chapter primarily covers how to evaluate replicate analyses of the same sample for accuracy and precision, but attention also is given to the determination of best line fits for standard curve data. A section of the chapter describes sensitivity and limit of detection as related to various analytical methods and regulatory agency policies. Additional information includes the proper use of significant figures, rules for rounding off numbers, and use of various test to reject grossly aberrant individual values.

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