응용 다변량 통계 행렬

Applied Multivariate Statistics Matrix algebra and random vector, sample geometry and random sampling, multivariate normal distribution, inference about mean, comparison of several multivariate means, multivariate linear regression model, principle components, factor analysis, covariance analysis, canonical correlation analysis, discrimination and classification, cluster analysis, computational techniques and use of SAS, Maple or other statistical packages and related topics. Lectures, 3 hours per week; lab 1 hour per week. Prerequisite(s): STAT (MATH) 1P11 or 1P12; STAT (MATH) 2P82 or permission of the instructor. Note: this course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term. Completion of this course will replace previously assigned grade and credit obtained in MATH 3P86. #

• Prerequisite(s): STAT (MATH) 1P11 or 1P12; STAT (MATH) 2P82 or permission of the instructor.
• Note: this course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term. Completion of this course will replace previously assigned grade and credit obtained in MATH 3P86. #