EEB 303 - Topics in Biology
Winter 2023, Section 001 - Introduction to Statistical Model Building in R
Instruction Mode: Section 001 is  In Person (see other Sections below)
Subject: Ecology and Evolutionary Biology (EEB)
Department: LSA Ecology & Evolutionary Biology
See additional student enrollment and course instructor information to guide you in your decision making.

Details

Credits:
4
Requirements & Distribution:
BS, NS
Advisory Prerequisites:
Recommended prerequisites will be established at the class level by the section instructors.
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May be repeated for a maximum of 6 credit(s). May be elected more than once in the same term.
Primary Instructor:
Start/End Date:
Full Term 1/4/23 - 4/18/23 (see other Sections below)
NOTE: Drop/Add deadlines are dependent on the class meeting dates and will differ for full term versus partial term offerings.
For information on drop/add deadlines, see the Office of the Registrar and search Registration Deadlines.

Description

This course is focused on the fundamental elements of data analysis in the fields of ecology and evolutionary biology. Students will learn how to interpret and model biological data with modern methods for estimation and inference using the R computing language. Topics include: introduction to R and Rmarkdown, data plotting, navigating errors/getting help, introduction to probability theory, demystifying probability distributions, introduction to deterministic relationships, likelihood-based inference, Bayesianism vs. Frequentism, and modes of inference.

 

This course satisfies the Quantitative Analysis II requirement for a number of Program in Biology majors. Please refer to your major program requirements or meet with a Program in Biology advisor to determine how the course will work for you.

 

Course Goals

1. Provide the necessary background and quantitative foundation to learn how to analyze biological data

2. Introduce R, a powerful programming environment for data analysis and presentation. Develop skills at writing R functions, with the goal of being able to perform advanced, computationally intensive analyses

3. Provide a conceptual introduction to model-based analysis

4. Lay the foundation for developing a sufficient and appropriate background to teach yourself new methods for data analysis as needed

Course Requirements:

The course assignments will consist of class participation, weekly problem sets, and group projects/presentations. Students will have the opportunity to work alone as well as in teams.

Class Format:

2 x 1.5 hr/wk lectures with in-class work.

Schedule

EEB 303 - Topics in Biology
Schedule Listing
001 (LEC)
 In Person
34037
Open
8
 
-
TuTh 11:30AM - 1:00PM
1/4/23 - 4/18/23
Note: Recommended Prerequisites: BIOLOGY 202 or STATS250

Textbooks/Other Materials

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Syllabi

Syllabi are available to current LSA students. IMPORTANT: These syllabi are provided to give students a general idea about the courses, as offered by LSA departments and programs in prior academic terms. The syllabi do not necessarily reflect the assignments, sequence of course materials, and/or course expectations that the faculty and departments/programs have for these same courses in the current and/or future terms.

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CourseProfile (Atlas)

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CourseProfile (Atlas)