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Statistical Inference for the Life Sciences


Course Description

Introductory statistics for students in the life sciences, including probability, discrete and continuous random variables, distributions, expectations, maximum likelihood, Bayesian inference, hypothesis testing, and linear regression. These topics will be mixed with applications of the statistical concepts to biological data. Statistical inference and real data analysis are implemented.


Athena Title

Stat Inference for Life Sci


Non-Traditional Format

This course will be taught 95% or more online.


Semester Course Offered

Offered spring


Grading System

A - F (Traditional)


Course Objectives

Students will learn concepts of statistical inference, particularly maximum likelihood and Bayesian inference, and apply techniques to biological data. Students will write and run computer simulations that will strengthen their knowledge of statistical concepts.


Topical Outline

Probability, random variables, probability distributions, expectation, maximum likelihood, hypothesis testing, Bayesian inference, and linear regressions.


Syllabus


Public CV