BIOL 4062

Analysis of Biological Data

Lec 01 selected

The course introduces students to techniques available for the analysis of biological data, including regression, general linear models and multivariate methods. Emphasis is on the practical use of these techniques rather than derivations. Students analyze real and realistic data sets, and are assessed on write-ups of these analyses.

Sections

Lecture

From the syllabus

From the Fall 2026 syllabus by Derek Tittensor and Hal Whitehead. Open the PDF

Grading

10%Report of analysis of data set 1aDue Oct 1
10%Report of analysis of data set 1bDue Oct 8
10%Report of analysis of data set 1cDue Oct 15
10%Report of analysis of data set 1dDue Oct 27
10%Report of analysis of data set 1eDue Nov 3
5%Description of data set 2 and proposed analysisDue Oct 22
30%Report of analysis of data set 2Due Dec 14
15%In-class test80 minutes; Dec 3

Course rules

Late work
Assignments lose 10% per weekday late without a medical or other legitimate explanation.
Missed work
Use the Student Declaration of Absence form, up to three times in the course.
Submission
Submit assignments through Brightspace by 16:30 on the due date.
Collaboration
Assignments must be completed individually; group work is not allowed.
Generative AI
Do not use generative AI for assignment writing; AI may assist with coding, but final code must be yours.
Attendance
Attend in-person lectures; they will not be recorded for later viewing.

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