Course Description
Biological research requires competency in the concepts and methods used to statistically test hypotheses. Emphasis is on the representation, manipulation and hypothesis testing of biological data with R. Students will use statistical analyses to solve problems encountered in biological analyses, such as analyzing sequencing data, sampling bias and phylogenetic relatedness.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
- Manipulate data, create visualizations, and perform basic statistical analysis using R and RStudio.
- Explain fundamental statistical concepts, including probability distributions, sampling theory, linear and generalized linear modeling frameworks.
- Explain the concept of likelihood and its applications in biostatistics.
Course Grading Information:
| Activity/Performance Measure | Percentage/Points |
|---|---|
| In-class activity report | 85% |
| Exam (3 exams) | 5% x 3 = 15% |
Grading Scale
| Percentage | Letter Grade |
|---|---|
| >= 93% | A |
| 90 to < 93% | A- |
| 87 to < 90% | B+ |
| 83 to < 87% | B |
| 80 to < 83% | B- |
| 77 to < 80% | C+ |
| 73 to < 77% | C |
| 70 to < 73% | C- |
| 67 to < 70% | D+ |
| 63 to < 67% | D |
| 60 to < 63% | D- |
| < 60% | F |
Attendance/Participation:
After each class, students will be required to submit your R products. This will be considered as Attendance for this course. As such, attendance will affect final course grade through the “in-class activity report.”
Course Materials Purchased by the Students:
No course materials are required.
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.