Abstract
Multivariate data analysis is the necessary tool to study complex phenomena and to analyze data of complex analytical techniques such as chromatography and spectro photometer. One of the most useful approaches in science to experimental data interpretation is the visualization of data. This fundamental operation cannot be simply performed with multivariate data. In this paper, an introduction to principal component analysis is offered as one of the method that can provide a meaningful representation of data in a projection plane. The choice of the projection plane corresponds to the determination of an optimal point of observation where multidimensional data can display most of their meaning.
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© 2010 Springer Science+Business Media B.V.
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Di Natale, C. (2010). With the Eye of the Beholder: An Introduction to the Observation of Multidimensional Data with the Principal Component Analysis. In: Malcovati, P., Baschirotto, A., d'Amico, A., Natale, C. (eds) Sensors and Microsystems. Lecture Notes in Electrical Engineering, vol 54. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3606-3_1
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DOI: https://doi.org/10.1007/978-90-481-3606-3_1
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Online ISBN: 978-90-481-3606-3
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