JMP Learning Library

Multivariate Methods

Learn statistical tools to explore and describe multi-dimensional data. Group together similar observations, reduce the number of variables in a data set to describe features in the data and simplify subsequent analyses. Uncover latent constructs in observed variables. Perform cross tabulation on groups of categorical responses such as those in survey data.

Survey Analysis (Cross Tabulation)Tabulate and analyze multivariable categorical data, such as from a survey, to compare responses and find relationships across multiple factors and categories.
ClusteringForm clusters (groups) of observations having similar characteristics (K-Means and Hierarchical Clustering).
Principal Components AnalysisReduce the dimensionality of a data set by creating new variables that are linear combinations of the original variables.

Factor AnalysisDescribe the variability in observed variables in terms of a smaller number of unobserved variables or factors.
Structural Equation ModelingTest causal theories and analyze relationships between observed variables and underlying latent constructs.

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