This two-part course will prepare students to apply quantitative techniques to the analysis of experimental data. To emphasize both practical and theoretical skills, the course will involve several hands-on workshops, and the completion of several projects will be required. Students will be well positioned to meet the emerging requirements of funding agencies for formally planned experiments and fully reproducible and documented data analysis methods.

Specific topics include: practical aspects of data formatting and management; graphical, mathematical and verbal communication of quantitative concepts; a review of statistics, with emphasis on the selection of appropriate statistical tests, the use of modern software packages, the interpretation of results, and the design of experiments; the formulation, evaluation, and analysis of mathematical models of biological function, with an emphasis on linear and non-linear regression, determination of model parameters, and the critical comparison of alternative models with regard to over-parameterization; an introduction to discrete- and continuous-time dynamic systems; analytical analysis and computational simulation of both linear and non-linear dynamic systems; an introduction of Markov processes, hidden Markov models, and Fourier analysis.


A fair degree of competence in algebra will be needed; you should be able to solve basic algebraic equations by hand. Some prior exposure to linear algebra and calculus will be helpful.

Some computer literacy is also needed; you should be able to e-mail, surf the web, install programs on your computer, work with a spreadsheet or other analysis package to manipulate and plot data. Prior exposure to any programming language will be helpful.

This course requires access to a computer to complete. For qBio I, you will need to be able to install and run the R statistical package, access the internet, print, etc. In qBio II, MATLAB software is used.

Books and Materials

qBio I: Students will need a laptop computer on which they can install software (R and R Studio), and bring to class. Both packages are free, and run on recent versions of Linux, Mac OS X, and Microsoft Windows.

qBio II: You will also need access to MATLAB, including the symbolic math toolbox (Simulink is not needed); students are encouraged to take advantage of academic and student discounts when licensing this software.

While the course does not require the use of a specific textbook, the following resources are recommended.

Intuitive Biostatistics, Harvey Motulsky
One of the most accessible introductions to statistics.

The Art of R Programming, Norman Matloff
One of the more comprehensive introductions to R.

R for Everyone, Jared Lander
Less in-depth than the above, but covers both basic use of R and basic statistics in a single, accessible text.

Nonlinear Dynamics And Chaos, Steven H. Strogatz
Contains a good introduction to dynamic systems and stability.

Practical Computing for Biologists, Haddock and Dunn
Covers many computing topics not covered in this class. Recommended for students considering a computational lab for a rotation or thesis.

R for Data Science, Grolemund and Wickham
Introduction to the tidyverse, focusing on importing, wrangling, exploring, and modeling your data and communicating the results. Also available online.

Teaching Assistants

For qBio I, there are five teaching assistants for this course: Shana Bergman, Dylan McNally, Ambrose Plante, Andrew Schaumberg, and Jazz Weisman. TAs will hold daily office hours. See schedule for times and locations. TAs will also be accessible via the Piazza platform.

Please make sure your questions are clear and complete, and that you have made and effort to find the answer yourself. The TAs are dedicated to helping you learn the concepts and skills taught in qBio, but they are not your Google fairies, and will not respond to questions that are easily answerable with a simple internet search.


This class will be graded according to the usual WCGS scale (Honors, High Pass, Low Pass, Fail).

For qBio I, grades will be determined based on several take-home problem sets, as well as a mid-term exam.

Assignments are due promptly at 11:59 PM on the due date. It is strongly suggested that you leave sufficient time to deal with technical issues (computers crashing, e-mail not working, hungry dogs, etc.) when handing in assignments.

For each of qBio I and qBio II, you have up to five days of extensions/grace periods for written assignments. They must be taken in whole day increments (even if you are just two minutes late for a particular assignment). In addition to some extra time for you, this policy is also intended to provide relief from technical issues as described above; please don’t ask for any additional extensions.

All students will also be asked to complete a survey at the end of the quarter, soliciting feedback on the course to inform its content and format in future years.