STAT 220 – Data Matters: Biostatistics for the Life Sciences

This course provides a foundational introduction to the principles and methods of statistics, with a specific focus on applications in the biological and life sciences. Students will learn the essential concepts of data collection, description, and inference. A significant portion of the course will be dedicated to hands-on data analysis using the R programming language, a powerful, open-source tool widely used in academic research and the biotechnology industry. All examples, exercises, and projects will be based on real-world biological data, enabling students to develop the skills necessary to design experiments, analyze data, and critically evaluate scientific literature in their field.

Upon successful completion of this course, students will be able to:

• Identify and classify different types of data and variables common in biological research.
• Distinguish between observational studies and controlled experiments and understand the principles of sound experimental design.
• Use the R and RStudio environment to manage data, perform calculations, and generate high-quality visualizations.
• Calculate and interpret descriptive statistics and select appropriate graphical summaries for different types of data.
• Understand and apply the fundamental concepts of probability, sampling distributions, and the Central Limit Theorem.
• Construct and interpret confidence intervals to estimate population parameters.
• Formulate and test statistical hypotheses using appropriate methods (t-tests, ANOVA, Chi-square tests).
• Analyze relationships between variables using correlation and simple linear regression.

Critically assess the statistical methods and conclusions presented in scientific publications.

Course descriptions may be subject to occasional minor modifications at the discretion of the instructor.