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Multivariate Data Analysis in Electroanalytical Chemistry
Author(s) -
Richards Edward,
Bessant Conrad,
Saini Selwayan
Publication year - 2002
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/1521-4109(200211)14:22<1533::aid-elan1533>3.0.co;2-t
Subject(s) - electroanalytical method , computer science , multivariate statistics , nanotechnology , data science , multivariate analysis , chemistry , electrode , materials science , machine learning , potentiometric titration
Data analysis is becoming an increasingly important aspect of electroanalytical chemistry, as voltammetric techniques and electrode arrays become ever more popular as diagnostic tools. Modern data analysis techniques promise to help us make full use of the large amounts of data collected, allowing electroanalytical chemists to get more out of their existing instruments, and paving the way for new measurement approaches. This article provides an overview of the most widely used multivariate techniques in electroanalysis, citing specific examples of how they have been applied, and looking at their relative merits. As in other areas of analytical science, no single technique is applicable to all applications and the running of controls and appreciation of the applications and limitations of each technique is essential.