Fall 2021 - STAT 605 G100

Biostatistical Methods (3)

Class Number: 5101

Delivery Method: In Person


  • Course Times + Location:



  • Exam Times + Location:

    Oct 18, 2021
    12:30 PM – 2:20 PM

    Nov 22, 2021
    12:30 PM – 2:20 PM

    Dec 9, 2021
    7:00 PM – 10:00 PM

  • Prerequisites:

    Any course in Statistics. Open only to students in departments other than Statistics and Actuarial Science.



Intermediate statistical techniques for the health sciences. Review of introductory concepts in statistics and probability including hypothesis testing, estimation and confidence intervals for means and proportions. Contingency tables and the analysis of multiple 2x2 tables. Correlation and regression. Multiple regression and model selection. Logistic regression and odds ratios. Basic concepts in survival analysis. Students with credit for STAT 305 may not take this course for further credit.


STAT Workshop Coordinator: Marie Loughin

Course Details:
Asynchronous and online.

Course Outline:

This upper-division course provides an opportunity for the further development of analytic skills acquired in basic courses in statistics and the health sciences. It concentrates on the relatively few techniques that are currently most used in health research, but it also seeks to provide a conceptual basis for understanding other techniques. The course focuses on unifying principles and widely applicable methods as opposed rote memorization of an array of unrelated ad-hoc procedures. The material is presented descriptively, from the point of view of understanding and practical use. 

The emphasis of the course is on analysis (rather than design) of observational studies where there is one outcome variable of primary interest and where the data are made up of multiple independent observations. Important areas not covered are: classical multivariate analysis (e.g., factor analysis, discriminant analysis, etc.), longitudinal data analysis, time series, random effects models, and experimental design considerations (e.g., Latin squares, etc.).


By the end of the course the participant should: 

1. understand the concept of a statistical model and how such models correspond to specific hypotheses or questions,
2. be able to interpret the results of an analysis in relation to the original questions or hypotheses that motivated the analysis,
3. be familiar with data analysis methods commonly used in health sciences and understand the basic limitations of competing methods,
4. understand and be able to critique the analysis methods described in published health research papers,
5. be able to communicate effectively with statistical consultants. 


The scheduling of the following topics is approximate: 

1. Review of introductory statistics from the pre-requisite course: Hypothesis testing, estimation and confidence intervals for means and proportions.
2. Review of basic concepts of probability with applications including diagnostic testing, sensitivity and specificity, the relative risk and the odds ratio.
3. Contingency Tables: The Chi-square test, r x c tables, multiple 2x2 tables, Simpson's paradox, Mantel- Haenszel method.
4. Correlation and simple linear regression: Regression concepts, estimation and testing for regression coefficients, evaluation of the model.
5. Multiple linear regression: Inference for regression coefficients, confounding and interaction, indicator variables, model selection, prediction, model assumptions and checking.
6. Logistic regression: Odds ratios, inference for regression coefficients, model assumptions, case-control studies.
7. Time permitting: Survival analysis including life tables, censoring, Kaplan-Meier method, log-rank test.

Mode of teaching:

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



  • Quizzes/HW Assignments 35%
  • Midterm Exam (in scheduled class meeting times) 30%
  • Final Exam (in scheduled class meeting times) 35%


There will be no make-up midterms.

Above grading is subject to change.


Student participation in this course will require computer equipment and a reliable internet connection. You may be requested to turn on audio and/or video during certain instructional activities, that may include tests and examinations, though exceptions will be accommodated. If you request such an exception for personal reasons, you must do so in writing to the course instructor by the end of the first week.

Tech Requirements for online course STAT 305/605:

To be able to complete the online class successfully, at a minimum you will need a personal computer, access to the internet, a webcam, and a microphone to take online exams.

Zoom will be used to proctor the exams.



Access to high-speed internet.

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.