Chemometrics: Mathematics and Statistics in Chemistry
Springer Science & Business Media, Oct 31, 1984 - Science - 485 pages
At a time when computerized laboratory automation is producing a da ta explosion, chemists are turning to applied mathematics and statistics for the tools to extract useful chemical information from data. This rush to find applicable methods has lead to a somewhat confusing body of literature that represents a barrier to chemists wishing to learn more about chemometrics. The confusion results partly from the mixing of chemical notation and nomenclature with those of statistics, applied mathematics and engineering. Additionally, in the absence of collaboration with mathematicians, chemists have, at times, misused data analysis methodology and even reinvented methods that have seen years of service in other fields. The Chemometrics Society has worked hard to solve this problem since it was founded in 1974 with the goal of improving communications between the chemical sciences and applied mathe matics and statistics. The NATO Advanced Study Institute on Chemometrics is evidence of this fact as it was initiated in response to a call from its membership for advanced training in several areas of chemometrics. This Institute focused on current theory and application in the new field of Chemometrics: Use of mathematical and statistical methods, Ca) to design or select optimal measurement procedures and experiments; and Cb) to provide maximum chemical information by analyzing chemical data. The Institute had two formal themes and two informal themes.
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Anal analysis analytical applications assumed average calculated calibration called Chem chemical Chemistry Chemometrics clusters coefficients combination components compounds considered contains correlation corresponding defined described detection determination discussed distance distribution effect elements equal equation error estimated example experimental experiments factor Figure function give given important increase indicated interval ITALY known laboratory limit linear mathematical matrix mean measurements methods noise objects observations obtained optimal original parameters peak plane plot points possible practice prediction present problem procedure produce projection properties reference regionalized represent residuals response samples separation shown shows signal significant SIMCA similar simplex solution space standard statistical structure sum of squares theory tion usually values variables variance weights
Page ii - NATO ASI Series Advanced Science Institutes Series A series presenting the results of activities sponsored by the NATO Science Committee, which aims at the dissemination of advanced scientific and technological knowledge, with a view to strengthening links between scientific communities The series is published by an international board of publishers in conjunction with...