Natural Science 0265 - Statistics and Experimental Design

This course is an introduction to descriptive and inferential statistics with examples drawn primarily from the fields of medicine, public health, and ecology. The approach is applied and hands-on; students are expected to complete two problem sets each week, collect and analyze data as a class, and design and carry out their own examples of each analysis in four review exercises. We cover description, estimation and hypothesis testing (z-scores, t-tests, chi-square, correlation, regression, and analysis of variance). More advanced techniques such as multi-way ANOVA and multiple regression are noted but not covered in detail. We also discuss the role of statistics in causal inference though the emphasis of the course is on practical applications in design and analysis. The course text is The Basic Practice of Statistics by David S. Moore; students use the statistical package Minitab to conduct data analyses.

Quantitative Skills In this course, students can expect to spend 6-8 hours weekly on work and preparation outside of class time.