STATS 767 : Foundations of Applied Multivariate Analysis

Science

2020 Semester One (1203) (15 POINTS)

Course Prescription

Fundamentals of exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.

Course Overview

Analysis of data with more than one response variable, including high dimensional cases with hundreds or thousands of responses. The course focuses on the use of software and the interpretation and presentation of results. Exploratory and descriptive techniques including principal components, canonical variates, clustering, and multidimensional scaling; with associated visualizations. Non-Euclidian distances and their uses. Inference for differences between groups, and associations between groups of variables, using both permutation testing and parametric methods. Methods for dealing with multiple testing including control of the false discovery rate. This course includes a project where the student will analyse a dataset of their choice using skills used in this course and prerequisite courses, and prepare written and oral reports.

Course Requirements

Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208 Restriction: STATS 302

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Graduate Profile: Master of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Select an appropriate multivariate procedure based on a description of the data and questions of interest, and justify the choice made. (Capability 3)
  2. Perform correctly multivariate procedures in a software package, and write justifications for choices made in the course of the analysis. (Capability 1)
  3. Identify the assumptions of their analysis, and means of checking these assumptions. (Capability 2)
  4. Produce visualizations of multivariate data, including appropriate lables and captions, and use them appropriately in written and oral reports. (Capability 4)
  5. Summarise the conclusions of a multivariate procedure orally and in writing, using nontechnical language. (Capability 4)

Assessments

Assessment Type Percentage Classification
Quizzes 5% Individual Coursework
Assignments 20% Individual Coursework
Test 15% Individual Test
Project 20% Individual Coursework
Final Exam 40% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Quizzes
Assignments
Test
Project
Final Exam

50% required on exam

Learning Resources

Course book will be provided.

Special Requirements

Midterm will be in class time.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 2 hours of lectures, a 1 hour tutorial, 3 hours of reading and thinking about the content and 4 hours of work on assignments and/or test preparation.

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page: https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Based on previous comments, we will spend more time discussing the production and interpretation of  the graphs we make in the course. 

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html).

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 20/12/2019 01:07 p.m.