This course will be an introduction to descriptive and inferential statistics, with examples drawn from the fields of ecology, agriculture, public health, and clinical medicine. The approach will mainly be applied and hands-on; students will complete a workbook of statistical problems, collect and analyze data as a class, design and carry out small individual projects, do weekly problem sets plus revisions, and read and interpret data from the literature. We will learn to use common computer packages for statistical analysis: Excel and Minitab. Topics will include description, estimation, and basic techniques for hypothesis testing: z-scores, t-tests, chi-square, correlation, regression, one-way and two-way analysis of variance, and odds ratios. More advanced techniques such as multi-way anovas and multiple regression will also be briefly noted. We will also discuss the role of statistics in the scientific method and the philosophy of science, although the emphasis of the course will be on practical applications in design and analysis.