Fall 2020 - STAT 685 G100

Applied Time Series Analysis (3)

Class Number: 3838

Delivery Method: In Person

Overview

  • Course Times + Location:

    Mo 5:30 PM – 6:20 PM
    REMOTE LEARNING, Burnaby

    Th 4:30 PM – 6:20 PM
    REMOTE LEARNING, Burnaby

  • Exam Times + Location:

    Dec 19, 2020
    7:00 PM – 10:00 PM
    REMOTE LEARNING, Burnaby

  • Prerequisites:

    STAT 302 or STAT 305 or STAT 650 or BUEC 333 or permission of instructor. Open only to graduate students in departments other than Statistics & Actuarial Science.

Description

CALENDAR DESCRIPTION:

Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models.

COURSE DETAILS:

Outline:

  1. Autocorrelation, seasonality, and trends in time series and their impacts on standard statistical inference techniques.
  2. Autoregressive models: definition, model formulation, and data analysis
  3. Moving average models: definition model formulation, and data analysis
  4. ARIMA models: definition, model formulation, and data analysis
  5. Introduction to forecasting with linear time series models
  6. Introduction to nonparametric fitting of trends and cycles to time series data

Mode of teaching:

  • Lecture: A mix of synchronous and asynchronous. (Some lectures will be synchronous, others will be asynchronous but with deadlines.)
  • Stats Workshop/tutorial: Synchronous
  • Quizzes: TBD; dates Synchronous
  • Final exam: TBD; date Synchronous

Grading

  • Assignments 30%
  • Midterm 1 15%
  • Midterm 2 15%
  • Final Exam 35%
  • Participation 5%

NOTES:

Above grading is subject to change.

Materials

MATERIALS + SUPPLIES:

Access to high-speed internet, webcam, microphone.
This course will using R, a statistical computing software. R Studio and the R statistical software can be downloaded free of charge from https://www.rstudio.com/ and https://cran.r-project.org/, respectively.

REQUIRED READING:

Required Textbook:

Time Series Analysis with Applications in R (2nd ed.)
by Jonathan D. Cryer and Kung-Sik Chan. Publisher: Springer

  • Book is available on-line for free through the SFU Libarary
E-Book ISBN: 978-0-387-75959-3
Hardcover ISBN: 978-0-387-75958-6
Softcover ISBN: 978-1-4419-2613-5

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

TEACHING AT SFU IN FALL 2020

Teaching at SFU in fall 2020 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).