Modern biology is a quantitative and complex science. Pick up any recent issue of a journal in the biological sciences and you will be confronted with sophisticated mathematical and statistical analysis. Thus, biometry (statistics applied to biology) is a fundamental part of the training of any professional biologist. All phases of research in biology, including design, data collection, analysis, and interpretation of published results, depend on an understanding of statistical principles and statistical methods.

This course is designed to provide graduate students with basic skills in the statistical analysis of biological data. Lecture topics include descriptive statistics, frequently used distributions (e.g., binomial, Poisson), goodness of fit, tests of independence, analysis of variance, nested and repeated measures analysis, analysis of covariance, regression, correlation, nonparametric alternatives, power analysis, and Bayesian statistics. The entire course will emphasize practical solutions for the analysis of biological data. This course is also useful for graduate students in other sciences.