Fall 2019 - ECON 333 D100

Statistical Analysis of Economic Data (4)

Class Number: 10286

Delivery Method: In Person


  • Course Times + Location:

    Sep 3 – Dec 2, 2019: Mon, 10:30 a.m.–12:20 p.m.

    Sep 3 – Dec 2, 2019: Wed, 10:30–11:20 a.m.

  • Exam Times + Location:

    Dec 9, 2019
    Mon, 12:00–3:00 p.m.

  • Prerequisites:

    ECON 103 or 200; ECON 105 or 205; BUS (or BUEC) 232 or STAT 270; MATH 157; 60 units.



An introduction to the use and interpretation of statistical analysis in the context of data typical of economic applications. Students with a minimum grade of A- in BUS (or BUEC) 232 or STAT 270 can take ECON 333 after 30 units. Students seeking permission to enroll based on their BUS (or BUEC) 232 or STAT 270 grade must contact the Undergraduate Advisor in Economics. Students with credit for BUEC 333 may not take this course for further credit. Quantitative.


This course will introduce you to the statistical analysis of economic data: econometrics.  We will focus on linear regression, which is by far the most common method for analyzing the relationship between two or more variables.  The main things you will learn in this class are how to apply regression methods to economic data and how to interpret the results of econometric analysis.  You will also get some experience using statistical software and establish a foundation for further econometric study.  

There will be regular graded assignments consisting of both exam-type questions and computer exercises.  You are expected to work independently on the assignments.  Cheating of any kind will result in at least a failing grade in the course.   The computer exercises will get you doing some real econometric analysis using the R software package.  R is installed on the lab computers; details on lab hours and procedures will be announced in the first week of class. R is open source, so you can freely download a copy for your own use here: https://www.r-project.org. I encourage you familiarize yourself with R before the start of the semester. You’ll find a good introduction here: https://www.r-econometrics.com/rbasicsintro/  

There will be a course website on Canvas. It is your responsibility to check it regularly.  This is where assignments, readings, etc. will be posted.  

I encourage you to prepare for BUEC 333 by reviewing material from your introductory statistics course.  Concentrate your review on probability distributions (especially sampling distributions) and hypothesis testing.  Appendices B and C of Wooldridge are a good summary of this material, and I strongly encourage you to read them before the semester begins.


  • Tutorial participation 10%
  • Assignments 25%
  • Midterm 30%
  • Cumulative final exam 35%



Jeffrey M. Wooldridge, “Introductory Econometrics: A Modern Approach” (7th edition), Cengage Learning, 2019.

Department Undergraduate Notes:


Students requiring accommodations as a result of a disability must contact the Centre for Accessible Learning (CAL) at 778-782-3112 or caladmin@sfu.ca.

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