Abstract
Analysis of information, resulting from different research programs, particularly the statistical procedures, may broadly be classified into univariate analysis and multivariate analysis. In univariate analyses, we consider one variable at a time contrary to the varied number of variables in multivariate analyses. The simplest case of multivariate analysis is the bivariate analysis, in which two variables are considered together. The variables that we consider in agriculture, economics, anthropology, sociology, psychology, management, etc., tend to move together, and as such multivariate analysis is more useful. Univariate analysis throws light on one character only, but to explain the relationship, interdependence, and relative importance of different variables, multivariate analyses would be more appropriate.
Keywords
- Powerful Multivariate Technique
- Multiple State Variables
- Unweighted Pair-group Centroid
- Cattell's Scree Test
- Canonical Variables
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2013 Springer India
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Sahu, P.K. (2013). Multivariate Analysis. In: Research Methodology: A Guide for Researchers In Agricultural Science, Social Science and Other Related Fields. Springer, India. https://doi.org/10.1007/978-81-322-1020-7_12
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DOI: https://doi.org/10.1007/978-81-322-1020-7_12
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Publisher Name: Springer, India
Print ISBN: 978-81-322-1019-1
Online ISBN: 978-81-322-1020-7
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