STAT 3336C Applied Multivariate Statistics

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The STAT 3336C Applied Multivariate Statistics course introduces students from different statistical backgrounds to the basic concepts of multivariate statistics. It will discuss the assumptions, limitations, and use of basic techniques such as cluster analysis, principal component analysis, and factor analysis, and how these methods are implemented in R. In addition to theoretical development, the emphasis will be on intuitive understanding and understanding. Apply these techniques to real student datasets.

Students who complete this course should be able to:

• In accordance with the specified multivariate data and research objectives, select appropriate methods for multivariate data analysis;
• Write SAS and/or Minitab programs for multivariate data analysis;
• Interpret the results of multivariate data analysis.

This is an asynchronous online graduate course. In this course, we will explore various statistical methods for multivariate data, including multivariate t-test and analysis of variance, dimensionality reduction techniques (such as principal component analysis, factor analysis, normative correlation analysis, and classification and clustering techniques).

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