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Introduction to Statistics for Life Sciences
STAT 102

Course Information

Description

This course introduces statistical inference and computing through applications in public health, medicine, and the life sciences. Topics include data visualization, data wrangling, principles of data collection, probability, estimation, hypothesis testing, and regression modeling. Students will develop both technical skills and statistical literacy, with a strong awareness of the ethical issues that arise when collecting, analyzing, and communicating data. The course prepares students to be responsible statistical practitioners, equipped to learn and apply field-specific methods while critically evaluating how analyses are conducted and how results are communicated. Active learning is central to the course: students prepare through videos and pre-class assignments, then engage in collaborative problem-solving during class meetings. Students will learn a reproducible workflow for analyzing data with the statistical language R. No prior statistics or programming experience is required.

Course Notes

For Spring 2026, STAT 102 sections will meet in the following locations: STAT 102 D001: Th 12-1:15pm, Maxwell-Dworkin (MD) 206 STAT 102 D002: Th 1:30-2:45pm, MD 206 STAT 102 D003: F 10:30-11:45am, MD 134A

School Faculty of Arts & Sciences
Credits 4
Cross Reg

Available for Harvard Cross Registration

Department Statistics
Course Component Lecture
Subject Statistics
Grading Basis FAS Letter Graded
Course Requirements Cannot be taken for credit if STAT 100, STAT 104, STAT 111, STAT 139, STAT 149, or STAT 244 already complete.
General Education N/A
Quantitative Reasoning with Data Yes
Divisional Distribution Science & Engineering & Applied Science
Course Level For Undergraduate and Graduate Students