ABSTRACT
This chapter examines topics related to modeling data for calibration and analysis purposes. It discusses the need for and general strategy of instrument calibration and describes the order of the model chosen to fit the data. The chapter explores the statistical confidence of a data point. Calibration is the process whereby specific inputs are applied to a measurement system and the corresponding outputs are measured. The purpose of calibration and modeling is to relate the measured quantity to the measurand via some form of mathematical relationship. In the calibration process, the mathematical equations used to model the process work on the specifics of the input–output process of the measurement system. In many aspects, data modeling and developing calibration mapping are similar processes. The least squares process provides the best estimate for the parameters to specify a model. In addition to residual plots, numeric indicators can be used as well to indicate the quality of the modeling process.
