The Advantages of Multivariate Analysis

Multivariate techniques are used to study datasets in consumer and market research, quality control and quality assurance, process optimization and process control, and research and development. These techniques are particularlyimportant in social science research because social researchers are generally unable to use randomized laboratory experiments, like those used in medicine and natural sciences. Here multivariate techniques can statistically estimaterelationships between different variables, and correlate how important each one is to the final outcome and where dependencies exist between them.

Because most data analysis tries to answer complex questions involving more than two variables, these questions are best addressed by multivariate statistical techniques. There are several different multivariate techniques to choosefrom, based on assumptions about the nature of the data and the type of association under analysis. Each technique tests the theoretical models of a research question about associations against the observed data. The theoreticalmodels are based on facts plus new hypotheses about plausible associations between variables.

Multivariate techniques allow researchers to look at relationships between variables in an overarching way and to quantify the relationship between variables. They can control association between variables by using cross tabulation,partial correlation and multiple regressions, and introduce other variables to determine the links between the independent and dependent variables or to specify the conditions under which the association takes place. This gives a muchricher and realistic picture than looking at a single variable and provides a powerful test of significance compared to univariate techniques.

(Source: www.ehow.com/info_8247893_multivariate-techniques-advantages-disadvantages.html)

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