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| STAT 46800 - Applied Multivariate Analysis |
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Credit Hours: 3.00. A detailed exposition of some of the more commonly used multivariate statistical techniques, including the geometric intuition underlying their use. Familiarity with the notation and the basic operations of matrix algebra, and with the standard univariate statistical procedures is assumed. Topics include dimension reduction techniques (principal components, factor analysis, and canonical correlation), clustering, classification, neural network, and structural equation models. Typically offered Fall Spring.
3.000 Credit hours Syllabus Available Levels: Undergraduate, Graduate, Professional Schedule Types: Distance Learning, Lecture Offered By: Regional Campus Only Course Attributes: Upper Division May be offered at any of the following campuses: Northwest- Westville Northwest- Hammond Learning Outcomes: 1. Distinguish principal components and factor analysis designs. 2. Analyze designs to study variance. 3. Identify the appropriate design for a dataset. 4. Communicate results. |
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