# Multivariate Analysis

Probability and Statistics > Multivariate Analysis

## What is Multivariate Analysis?

Multivariate analysis is used to study more complex sets of data than what univariate analysis methods can handle. This type of analysis is almost always performed with software (i.e. SPSS or SAS), as working with even the smallest of data sets can be overwhelming by hand.

Multivariate analysis can reduce the likelihood of Type I errors. Sometimes, univariate analysis is preferred as multivariate techniques can result in difficulty interpreting the results of the test. For example, group differences on a linear combination of dependent variables in MANOVA can be unclear. In addition, multivariate analysis is usually unsuitable for small sets of data.

There are more than 20 different ways to perform multivariate analysis. Which one you choose depends upon the type of data you have and what your goals are. For example, if you have a single data set you have several choices:

Although there are fairly clear boundaries with one data set (for example, if you have a single data set in a contingency table your options are limited to correspondence analysis), in most cases you’ll be able to choose from several methods.

Cluster analysis showing three groups.

Click on a topic to read about specific types of multivariate analysis:

Related:

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Statistical concepts explained visually - Includes many concepts such as sample size, hypothesis tests, or logistic regression, explained by Stephanie Glen, founder of StatisticsHowTo.