Analytical chemistry deals with both qualitative and quantitative measurements, although modern approaches are more inclined towards quantitative science. In analytical laboratories, the measurements are usually made on a small group of representative samples to determine the presence and concentration of target analytes. Following data collection, the results are tabulated to evaluate the quality of the data. An important area in evaluating analytical data is represented by statistical approaches, which should not be considered only for evaluating the results of experiments, but also in the planning and design of experiments. The design and optimization process should include the identification of those experimental factors and then combine them in an optimal way to obtain the best sensitivity and selectivity among other factors. The major quantitative chemical problems can also be performed with chemometric measurements. The starting point of multivariate measurements is usually represented by principal component analysis (PCA), which can reduce the dimensionality of the data, eliminate false information, search for outliers, and more. The modern tools for various measurements are completely devoid of manual controls and are controlled by personal computers that record and manage the obtained data. In recent years, appreciable progress has been made, and in the most modern analytical chemistry laboratories, instruments not only allow quick and precise data calculations but also include instrument performance control and reporting of any malfunctions.

Advances in Chemical Analysis Procedures (Part II): Statistical and Chemometric Approaches

Locatelli, Marcello
;
Tartaglia, Angela;
2020

Abstract

Analytical chemistry deals with both qualitative and quantitative measurements, although modern approaches are more inclined towards quantitative science. In analytical laboratories, the measurements are usually made on a small group of representative samples to determine the presence and concentration of target analytes. Following data collection, the results are tabulated to evaluate the quality of the data. An important area in evaluating analytical data is represented by statistical approaches, which should not be considered only for evaluating the results of experiments, but also in the planning and design of experiments. The design and optimization process should include the identification of those experimental factors and then combine them in an optimal way to obtain the best sensitivity and selectivity among other factors. The major quantitative chemical problems can also be performed with chemometric measurements. The starting point of multivariate measurements is usually represented by principal component analysis (PCA), which can reduce the dimensionality of the data, eliminate false information, search for outliers, and more. The modern tools for various measurements are completely devoid of manual controls and are controlled by personal computers that record and manage the obtained data. In recent years, appreciable progress has been made, and in the most modern analytical chemistry laboratories, instruments not only allow quick and precise data calculations but also include instrument performance control and reporting of any malfunctions.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11564/727408
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