3975 (v.4) Applied Statistics 302


 

Area:Department of Mathematics and Statistics
Contact Hours:4.0
Credits:25.0
Lecture:3 x 1 Hours Weekly
Practical:1 x 1 Hours Weekly
Prerequisite(s):8128 (v.6) Linear Algebra 202 or any previous version
AND
8393 (v.8) Statistical Methods 201 or any previous version
AND
302315 (v.2) Mathematical Statistics 202 or any previous version
Introduction to multivariate statistical analysis. Review of matrix algebra. Random vectors, Mean vectors, covariance and correlation matrices. Multivariate normal distribution and its properties. Random samples from the multivariate normal and sampling distributions thereof. Inference for multivariate normal parameters, maximum likelihood estimation, GLM and inferences for GLMS, one-sample and two sample test of hypotheses on the mean vector; comparison of several mean vectors - multivariate analysis ofvariance (MANOVA), discriminant analysis. Analysis of multivariate data using statistical software like R and SAS.
YearLocationPeriodInternalArea ExternalCentral External
2003Bentley CampusSemester 2Y  

 

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