Description

This is an entry-to-intermediate level course of biostatistics aimed at scientists in the life sciences. No prior R programming experience is required. The course will introduce students to the basic concepts and statistical tests that are routinely encountered in analyzing scientific data in designed experiments, as opposed to the analysis of clinical or epidemiological type data. Following an introduction to probability, students will learn what statistical tests are appropriate and how to run them. Emphasis is on intelligent usage rather than mathematical formality. Standard tests such as t, z, chi squared, ANOVA analyses will be learned, as well as how power analyses and sample size calculation are performed. In addition, advanced topics in life sciences, including PCA, clustering, linear modeling, and machine learning methods will be covered. Another goal of this course will be to build familiarity with the basic R toolkit for statistical analysis and graphics.