STATS 767 Topics in Multivariate Analysis

Below description edited in year: 2018

Points: 15

Prereqs: 15 points from STATS 201, 207, 208, or BIOSCI 209

Restrictions: STATS 302

Credit: 40% exam, 20% project, 40% Coursework (15% Test, 20% Assignments, 5% quizzes). Must obtain 50% in final exam to pass.

For Advice: Beatrix Jones (Email: beatrix.jones@auckland.ac.nz | extn: 84790)

Taught: Second Semester City

Website: STATS 767 website

This course includes the material in STATS 302. It is intended for postgraduate students who have not already passed STATS 302. STATS 767 covers the exploratory analysis and modeling of multivariate data, with emphasis on the use of statistical software and reporting of results.

Topics studied include: Techniques for data display, dimension reduction and ordination, cluster analysis, multivariate regression and Analysis of Variance (MANOVA), Canonical Correlation, and Redundancy Analysis. The approach will be largely non-mathematical and practical, with an emphasis on the understanding of the techniques.

Disclaimer:
Although every reasonable effort is made to ensure accuracy, this information for the course year (2018), is provided as a general guide only for students and is subject to alteration. All students enrolling at the University of Auckland must consult its official document, the University of Auckland Calendar, to ensure that they are aware of and comply with all regulations, requirements and policies.