Abstract
Foundations of Experimental Data Analysis presents the most important procedures used in the analysis of sets of experimental data. It also describes the most efficient methods for estimating parameters. Fundamental concepts in probability theory and mathematical statistics are provided for background information in the first chapter. The book's second chapter presents a survey of algorithms from which factographic data on measured objects are acquired. Six fundamental linear models of measurement describing all known types of linear or linearized relations between directly observable parameters and determined ones are studied in their simple and mixed versions. The third chapter is devoted to the problems of analyzing measured data.
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