BI 255: Introduction to Biostatistics & Data Science
Bethune-Cookman University · Department of Natural Sciences
Mon / Wed / Fri, 50 min · Posit Cloud & R ·
About This Course
Course Description
An introduction to data science through the lens of biology. Students learn to collect, clean, visualise, and statistically analyse biological data using R, with no prior programming experience required. By the end of the semester, every student will have built a reproducible research poster in R.
What You Will Learn
- Programming fundamentals in R on Posit Cloud
- Data visualisation with ggplot2
- Hypothesis testing and statistical inference
- Regression, correlation, and model building
- Species diversity and community ecology analysis
- Spatial mapping and text analysis
Prerequisites
No programming experience required. Students should be comfortable using a web browser and creating folders on a computer.
Grading
- Bi-Weekly lab quizzes — 75%
- Final research poster — 25%
Lab Materials
Each lab is a self-contained Quarto document with worked examples, call-out boxes, and a knowledge check. Use the sidebar to browse all 34 labs by week — every page is fully reproducible in Posit Cloud.
Resources
Posit Cloud
All coding is done in your browser.
R for Data Science
Free online textbook by Hadley Wickham — an excellent companion reference.
ggplot2 Cheatsheet
RStudio’s official quick-reference card for data visualisation in R.
dplyr Cheatsheet
Quick-reference for data wrangling operations in the tidyverse.
BCU Library
Access databases and datasets, journals, and research support from the Carl S. Swisher Library.
Instructor
Dr. Rosie Stanbrook-Buyer
Assistant Professor, Department of Integrated Environmental Science & Natural Sciences
| stanbrookr@cookman.edu | |
| Office Hours | Use calendly to schedule |
| Posit Cloud | Workspace link distributed in first lab |
| Response Time | Within 48 hours on weekdays |