Fall 2021 - STAT 642 G100

Introduction to Statistical Computing and Exploratory Data Analysis - SAS (2)

Class Number: 5086

Delivery Method: In Person


  • Course Times + Location:

    Th 12:30 PM – 2:20 PM

  • Exam Times + Location:

    Dec 17, 2021
    3:30 PM – 6:30 PM

  • Prerequisites:

    STAT 285 or STAT 302 or STAT 305 or ECON 333 or equivalent. Open only to students in departments other than Statistics and Actuarial Science.



Introduces the SAS statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Students with credit for STAT 340 or STAT 342 may not take STAT 642 for further credit.


Course Outline:

SAS component

  1. What is SAS?
      - Downloading and installing
      - Overview of the system
  2. Data management in SAS
      a. Data input and structures
          - DATA step
          - Reading specially formatted files
          - Date/time/character formats and manipulations
          - Derived variables
          - Exporting
      b. Data access: from database systems using query languages
      c. Merging and reshaping data
          - sorting/subsetting (set/if/where statements)/ merging/transposing
          - processing using DO LOOPS and SAS arrays
          - modify variable attributes
  3. Data exploration and representation in SAS
          - basic procs (print, plot, tabulate, means, univariate, freq)
          - by statement and uses in analysis and simulation
          - output delivery system to extract information from analyses
  4. Data simulation in SAS

Mode of Teaching

  • Lecture: Synchronous/Asynchronous
  • Tutorial: Synchronous/Asynchronous
  • Quizzes and Midterm: Synchronous; Date: TBA
  • Final exam: Synchronous; date: TBA
  • Remote invigilation (Zoom, or other approved software) will be used.


  • Assignments 10%
  • Midterm 40%
  • *Final Exam (with an option to substitute part of the percentage assigned to the final exam with the completion of a project) 50%


Above grading is subject to change.



Required Text:

SAS and R, Data Management, Statistical Analysis, and Graphics, 2nd ed, 
by Ken Kleinman and Nicholas J. Horton, Publisher: CRC Press

Hard Copy ISBN: 9781466584495
eBook ISBN: 9781466584501
eBook Rental ISBN: 9781466584501

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:


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 2021 will involve primarily in-person instruction, with approximately 70 to 80 per cent of classes in person/on campus, with safety plans in place.  Whether your course will be in-person or through remote methods will be clearly identified in the schedule of classes.  You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).

Enrolling in a course acknowledges that you are able to attend in whatever format is required.  You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware 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.

Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the fall 2021 term.