Canonical correlation analysis is used to measure the strength of the association between the independent and independent sets of variables. This type of analysis is most helpful in validation of test results, wherein the researcher would determine which variables are significantly related, and upon determining this, run further canonical analysis with the identified significant variables (Hair, 1995:187)
Multiple regression, when applied to specific situations, could best answer problems wherein it must be determined which among the many extant factors are possibly contributing to a set of outcomes (dependent variables). For example, is variation in sales driven by prices, distribution, or advertising? Is individual perception about a political personality determined by psychographic or demographic profile? And which among the variables in each factor contribute strongly to the formation of this perception? Discriminant analysis is most useful in profiling specific groups of people or individuals based on specific characteristics, which may be demographic, psychographic, lifestyle, and specific categories defined by the researcher to be characteristic of the dependent variable (Malhotra, 1996:617)
Factor analysis helps the researcher determine and explain the relationships, specifically correlations, extant among the variables tested. Application of this type of analysis is most useful in market research, wherein psychographic factors and attitude statements are often treated as one set of variables, factor analyzed to generate a smaller set of variables that would somehow reflect, highlight, or explain differences among the variables and across respondent groups or profiles (Weiers, 1984:473)
Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical ...
Multivariate statistical analysis refers to multiple advanced techniques for examining relationships among multiple variables at the same time.
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Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable.
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Noun 1. multivariate analysis - a generic term for any statistical technique used to analyze data from more than one variable statistics - a branch of applied ...
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Lessons designed to teach the intermediate student how to use SPSS for multivariate statistical analysis.
Through the use of multivariate and bivariate analysis, market research experts can provide detailed interpretations of complex sets of data.
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Amazon.com: Multivariate Analysis (Probability and Mathematical Statistics) (9780124712522): Kanti V. Mardia, J. T. Kent, J. M. Bibby: Books