The modern technological ability to handle large amounts of information confronts the chemist with the necessity to re-evaluate the statistical tools he routinely uses. Multivariate statistics furnishes theoretical bases for analyzing systems involving large numbers of variables. The mathematical calculations required for these systems are no longer an obstacle due to the existence of statistical packages that furnish multivariate analysis options. Here basic concepts of two multivariate statistical techniques, principal component and hierarchical cluster analysis that have received broad acceptance for treating chemical data are discussed.
Uma introdução à análise exploratória de dados multivariados
Published 1998 in Química Nova
ABSTRACT
PUBLICATION RECORD
- Publication year
1998
- Venue
Química Nova
- Publication date
1998-07-01
- Fields of study
Chemistry
- Identifiers
- External record
- Source metadata
Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
- No references are available for this paper.
Showing 0-0 of 0 references · Page 1 of 1