We will study methods of analysis for data which consist of observations on a number of variables. The primary aim will be interpretation of the data, starting with the multivariate normal distribution and proceeding to the standing multivariate inference theory. Sufficient theory will be developed to facilitate an understanding of the main ideas. This will necessitate a good background in matrix algebra, and some knowledge of vector spaces as well. Computers will be used extensively, and familiarity with elementary use of SAS will be assumed. Grades will be based on a combination of class test and final examination, plus routine homework. Topics covered will include multivariate normal population, inference about means and linear models, principal components, and possibly some discussion of discriminant analysis, and factor analysis, if time and student interest permit.
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