Simon Fraser University
Engaging the World

Course Outlines

Summer 2021 - STAT 302 D100

Analysis of Experimental and Observational Data (3)

Class Number: 2070

Delivery Method: In Person

Overview

  • Course Times + Location:

    May 12 – Aug 9, 2021: Mon, 2:30–3:20 p.m.
    Burnaby

    May 12 – Aug 9, 2021: Thu, 2:30–4:20 p.m.
    Burnaby

  • Exam Times + Location:

    Aug 13, 2021
    Fri, 8:30–11:30 a.m.
    Burnaby

  • Prerequisites:

    One of STAT 201, STAT 203, STAT 205, STAT 270, or BUEC 232, with a minimum grade of C-.

Description

CALENDAR DESCRIPTION:

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.

COURSE DETAILS:

STAT Workshop Coordinator: Harsha Perera

Outline:

  1. Review: Important concepts from the first course in statistics will be reviewed.
  2. Simple linear regression: models summarizing the relationship between two quantitative variables. This unit includes the estimation and interpretation of model parameters, assessment of the model’s fit, inference, and prediction.
  3. Multiple regression: models in which several explanatory variables combine to help explain the variability in a quantitative response variable. This unit 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): models that allow the comparison of means of a quantitative response variable across groups defined by a categorical explanatory variable. This unit includes model assessment, inference methods for comparison of means, and tests for homogeneity of variances.
  5. Other topics may include analysis of covariance, the problem of multiple testing, and/or block designs.


Mode of teaching:

  • Lecture: synchonous (recorded)
  • Midterms: June 17 (14:30-16:20), July 22 (14:30-16:20)
  • Final exam: synchronous (date: TBA)

 

Grading

  • Assignments 20%
  • Midterm 1 20%
  • Midterm 2 20%
  • Final Exam 40%

NOTES:

You must pass the final exam to pass the course.

Above grading is subject to change.

Materials

MATERIALS + SUPPLIES:

You will need access to high speed internet and a webcam.

We will be using the R programming language, which you can access via Jupyter, an online platform, at https://sfu.syzygy.ca/. Alternatively, you can download R Studio and R statistical software free of charge from https://www.rstudio.com/ and https://cran.r-project.org/, respectively.

RECOMMENDED READING:

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

An e-version of the textbook available at vitalsource.com.

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 hhttps://www.sfu.ca/stat-actsci/all-students/other-resources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.

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 SUMMER 2021

Teaching at SFU in summer 2021 will be conducted primarily through remote methods, but we will continue to have in-person experiential activities for a selection of courses.  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).