Biology 300: Fundamentals of Biostatistics

January-April 2023

Please note that the Canvas site will be the main course site for students enrolled in the course. Please use that site to get the latest announcements, assignments, etc.

Here is some general info about the course:

Instructors: Dr. Kaitlyn Gaynor & Dr. Darren Irwin

TAs: Kenny Askelson, Alireza Ghaseminejad, Penny Kahn, Javad Meghrazi, Rashika Ranasinghe, Emily Trudeau


Tuesdays and Thursdays 2:00-3:20 p.m., room 100 of the Neville Scarfe building (SCRF 100)

For your convenience, we will post slides from lectures, usually before we present the material. Note, however, to facilitate effective teaching we often tinker with lecture material, so the details of what is presented and the order may change. Make sure you pay attention in class and take notes–online lecture material should not be viewed as a substitute for attending class.


BioSciences 2004, starting second week of term (Jan. 16-20). Here are the lab sections, in chronological order:

  • L24: Mon 9-11am (TA: Emily Trudeau)
  • L21: Mon 12-2pm (TA: Kenny Askelson)
  • L22: Tue 8-10am (TA: Alireza Ghaseminejad)
  • L23: Tue 11am-1pm (TA: Emily Trudeau)
  • L25: Wed 9-11am (TA: Rashika Ranasinghe)
  • L29: Wed 2-4pm (TA: Javad Meghrazi)
  • L26: Thu 8-10am (TA: Penny Kahn)
  • L30: Thu 11am-1pm (TA: Penny Kahn)
  • L27: Fri 9-11am (TA: Javad Meghrazi)
  • L28: Fri 12-2pm (TA: Alireza Ghaseminejad)


The textbook (The Analysis of Biological Data 3rd Ed., by Whitlock and Schluter) is available for purchase at the UBC bookstore, as either a Hardcover or an E-book (which is much less expensive). If you have an earlier edition, this will work for much of the learning, although you will need access to a copy of the 3rd edition for some assignment problems. (A copy is on reserve in the Woodward library.)

If you don’t yet have the 3rd edition and want to learn some of the initial material, the first three chapters from the 2nd edition are available here, here, and here.)

Exams, Homework, and Grading

To promote fairness for all students, we will answer questions about the scope and format of exams only when the whole class has the opportunity to hear the answer (i.e., in lecture).

Mid-term exam: March 7, in class. The exam will include both short-answer questions and some longer-answer questions (e.g., hypothesis testing or estimation), some involving calculation. You are allowed to use a simple calculator, and will be provided the formulae sheet and statistical tables (you should practice using them in advance). We will provide more details on the scope of the midterm about 2 weeks before the exam.

If you miss the midterm with a legitimate excuse (either by pre-arrangement or an acceptable medical or other emergency), the final exam grade will be used in place of the midterm in the final grade assessment, after adjustment to take into account the relative difficulty of the midterm and final.

Lab exam: The lab exam will be held during the last session of your tutorial, in person in room Biosci 2004.

Final exam: time and place to be set by Student Services. The final exam will cover material from the whole course. It will last 2.5 hours.

The course grade will be calculated roughly as follows:
Assignments: 12.5%
Labs: 12.5%
Midterm: 25%
Lab exam: 15%
Final: 35%

Throughout the course, there will be two types of weekly exercises. The goal of these are to get you lots of practice with the ideas, concepts, and techniques you learn about in the lectures and in the lab.

For the Assignments, you will be given a couple of questions each week that build upon the material discussed in lecture; these will involve a combination of conceptual questions (entered directly into Canvas) and calculation questions that you will be asked to do with pen and paper and upload into Canvas. We will typically announce each homework assignment on a Friday and these will be due the following Friday.

For the Labs, you will enter the answers to all of the questions at the end of each Lab into Canvas. You will be expected to analyze data in R as part of the exams so this is a great chance to become comfortable with the language and how to interpret the output of the various functions you will need. These will also be due Friday.

Policy on academic honesty:
Your performance on the exams, homework, and assignments is expected to reflect your own work. University policy dictates stern penalties (e.g. suspension or expulsion) for those who misrepresent another person’s work as their own or allow such misrepresentation of their own work. On homework and lab assignments, it is acceptable to work in groups, but it is not acceptable to copy another’s work or allow your work to be copied.