Spring 2021 - STAT 302 D100

Analysis of Experimental and Observational Data (3)

Class Number: 3315

Delivery Method: In Person


  • Course Times + Location:

    Mo 12:30 PM – 2:20 PM

    We 12:30 PM – 1:20 PM

  • Exam Times + Location:

    Apr 20, 2021
    3:30 PM – 6:30 PM

  • Prerequisites:

    One of STAT 201, STAT 203, STAT 205, STAT 270, or BUEC 232.



The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies. This course may not be used to satisfy the upper division requirements of the Statistics major or honours program. Quantitative.


STAT Workshop Coordinator: Harsha Perera


  1. Review: Important concepts from the first course in statistics will be reviewed.
  2. Simple linear regression (SLR): models summarizing the relationship between two quantitative variables. This includes the estimation and interpretation of model parameters, assessment of the model’s it, inference, and prediction.
  3. Multiple regression: constructing models in which several explanatory variables combine to help explain the variability in a quantitative response variable. This includes model assessment, comparison of two regression lines, interactions between explanatory variables, and multicollinearity. Additional topics may include identifying unusual points, variable selection, and/or coding categorical predictors.
  4. Analysis of variance (ANOVA): Use of models to compare means of a quantitative response variable between groups de ined by a categorical explanatory variable (e.g. a treatment variable). Includes model assessment and inference for comparison of means. If time allows, other topics in ANOVA may be included, such as analysis of covariance, tests for homogeneity of variances, the problem of multiple testing, and/or block designs.

Mode of teaching:

  • Lecture: synchonous (recorded)
  • Tutorials:synchronous (recorded, with scheduled bi-weekly quizzes)
  • Midterms: NA
  • Final exam: synchronous; date: TBA
  • Remote invigilation: Zoom will be used.



  • Quizzes (best 5 out of 6) 65%
  • Final Exam 35%


You must pass the final exam to pass the course.

Above grading is subject to change.



Access to high speed internet and a webcam


STAT2 Modeling with Regression and ANOVA, 2nd ed. by Cannon, Cobb, Hartlaub, et al. Publisher: Macmillan Learning

There may be an e-version of the textbook available, please check the Canvas course for details.

Department Undergraduate Notes:

Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or csdo@sfu.ca

Tutor Requests:
Students looking for a Tutor should visit http://www.stat.sfu.ca/teaching/need-a-tutor-.html. We accept no responsibility for the consequences of any actions taken related to tutors.

Registrar Notes:


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 spring 2021 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).