STATS 727 : Foundations of Applied Time Series Analysis


2021 Semester One (1213) (15 POINTS)

Course Prescription

Fundamentals of applied time series analysis. Topics include: components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas are presented.

Course Overview

STATS 727 covers the analysis of Time Series data. Initially, the unique features of Time Series data are investigated. Then the main focus is on how to model Time Series data and use the models to forecast future values. Since there are many different models that can be fitted to a given Time Series, techniques to determine which model gives the most accurate predictions are also developed. By the end of STATS 727, students should be able to model and predict discrete univariate Time Series data and have an understanding of more complicated Time Series models that involve multivariable Time Series and/or more advanced modelling techniques mainly selected from a commercial (finance or economic) context. The course also involves students researching an area in Time Series not covered in the course and writing a Report and sitting a Test on their chosen topic. This course will be very useful for anyone wanting to be a Data Scientist as data scientists most common work will be forecasting for central and local government, businesses, not-for-profit charities, banks, finance companies, etc.

Course Requirements

Prerequisite: 15 points from BIOSCI 209, ECON 221, STATS 201, 207, 208, 707 Restriction: STATS 326

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Capability 6: Social and Environmental Responsibilities
Graduate Profile: Master of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Understand how Time Series data differs from other data types and what components are likely in a given set of Time Series data. (Capability 1)
  2. Communicate effectively on the results of Time Series models and forecasts in a concise manner. (Capability 4)
  3. Make informed decisions on future prospects using Time Series models and forecasts. (Capability 2, 3 and 6)
  4. Have will have sufficient exposure to more complex Time Series models to understand other modelling techniques not covered in the course. (Capability 5)
  5. Have the ability to research topics and methods in Time Series Analysis (Capability 1, 2, 3, 4 and 5)


Assessment Type Percentage Classification
5 Assignments 20% Individual Coursework
Online Quizzes 10% Individual Coursework
3 Tests 30% Individual Test
Research Essay 10% Individual Coursework
Final Exam 30% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
5 Assignments
Online Quizzes
3 Tests
Research Essay
Final Exam
Provided all coursework is handed in on time, the course plussage option is available:
Best Test Score: 33%
Final Examination: 67%

Key Topics

Introduction (outline) of the course
Special features of Time Series data
Non-stationary modelling
Stationary Time Series
SARIMA models
Advanced Topics in Time Series

Special Requirements

There are 2 Tests, each of 1 hr duration that will be held in the evenings (Week 5 and Week9).

Students overseas will sit their tests online with the standard University Rules applying.

Workload Expectations

This course is a standard [15] point course and students are expected to spend 12.5 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect [36] hours of lectures, [40] hours of reading and thinking about the content and [74] hours of work on assignments and/or test preparation.

Delivery Mode

Campus Experience

Attendance is expected at lectures to complete components of the course.

Lectures will be available as recordings.

The course will not include live online events.

Attendance on campus is required for the tests and the exam.

The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course book will be available on Canvas.
If you require a printed copy, they can be ordered and purchased from the Science Resource Centre.

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.

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.

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.


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.

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

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

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

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

Level 1: Delivered normally as specified in delivery mode.
Level 2: You will not be required to attend in person. All teaching and assessment will have a remote option.
Level 3 / 4: All teaching activities and assessments are delivered remotely.

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


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 27/04/2021 12:50 p.m.