Learning objectives
<br />PC training for data processing and interpretation in multivariate analysis(multivariate analysis, experimental design, optimization)
Prerequisites
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Course unit content
<br />Laboratory practice (computer elaboration) regarding data processing in multivariate systems, experimental design and optimization (principal component analysis, discriminant analysis, cluster analysis, K-full factorial design, fractional design, Yates algorithm, desirability curves, Simplex optimization.)
Full programme
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Bibliography
<br />J.N. Miller, J.C. Miller, "Statistic and Chemometrics for Analytical Chemistry" Prentice Hall, Harlow, England, <br />R. Todeschini, "Introduzione alla chemiometria", EdiSES, Napoli; <br />G. E. P. Box, W. G. Hunter, J. S. Hunter, "Statistic for Experimental" Wiley, New York.
Teaching methods
<br />Frontal lectures and laboratory practice
Assessment methods and criteria
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Other information
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2030 agenda goals for sustainable development
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