APST 755 - Multivariate Statistical Methods

(3 units)

Application of MANOVA and regression, principle component and factor analysis, discriminant, canonical correlations, and cluster analyses in sociology, life, and environmental sciences. Emphasis on SAS.

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. design and create cutting-edge-quality graphics/visualizations (including simulations) and tables for multivariate statistical methods using spreadsheets, statistical packages and special purpose programming.
2. report and interpret multivariate statistical methods in writing and in presentation format at a graduate level.
3. translate a research problem into multivariate statistical methods; formulate hypotheses; evaluate alternative regression estimators with respect to their precision, their robustness, and their compliance with assumptions, especially concerning distributions of residuals. Distinguish serious and trivial consequences of assumption violation. Defend their choice. Explain and deploy basic strategies for exploratory analysis and model building.
4. compute multivariate statistics using statistical packages; identify relevant estimates in output of a statistical package; identify implications of the results for the hypotheses; estimate and interpret the magnitudes of associations using both estimates, first differences and confidence intervals. Statistics include structural equation models; principle component and factor analysis, discriminant and cluster analysis, and canonical correlations.

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