This foundational class covers modes of reasoning used in quantitative sciences and mathematics. While learning the art of mathematical modeling, i.e. translating the physical systems/real-life situations into mathematics, we will apply problem-solving strategies to creatively solve problems and practice effective communication of mathematics. This process involves isolating the essential variables and interactions, setting up equations that constitute a model, running the model on a computer (we will use R: http://www.r-project.org/), and modifying the hypotheses in response to the model predictions. This process is helpful in many areas of science and social science because it forces you to carefully understand your assumptions, allows you to test and more deeply understand basic conceptual theories, and can help identify targeted experiments to fill gaps in the current understanding of the system.
This course is not a repetition of high school mathematics; rather, it places high school mathematics in a larger context and concentrates on the applications of mathematical thinking to the sciences. You do not need to know about logarithms or trig functions to take the course – we will develop these from the beginning – but you should be comfortable with topics like elementary algebra and drawing simple graphs.
Note: If you are accessing the course remotely you will need a tablet that you can write on so that you can participate in group work. Please talk to the instructor if this is a concern.
In this course, you will:
• Tackle unfamiliar problems individually and collaboratively with classmates
• Explore and communicate mathematics orally and in writing
• Develop mathematical models to represent real-world systems
• Create your own R programs to simulate your model results
• Develop a question, research the system, create a mathematical model, and communicate your results.
Delivery Method: Fully in-person
Course Level: 2000-level
M/Th 10:00AM - 11:50AM (Full-term)
Maximum Enrollment: 20
Course Frequency: Once a year
Categories: All courses , Fully In-Person , Mathematics
Tags: collaborative , computational biology , Environmental Studies