EPSY 5261 is designed to engage students in statistics as a principled approach to data collection, prediction, and scientific inference. Students first learn about data collection (e.g., random sampling, random assignment) and examine data descriptively using graphs and numerical summaries. Students build conceptual understanding of statistical inference through the use of simulation-based methods (bootstrapping and randomization) before going on to learn parametric methods, such as t-tests (one-sample and two-sample means), z-tests (one-sample and two-sample proportions), chi-square tests, and regression. This course uses pedagogical methods grounded in research, such as small group activities and discussion.
Attention undergraduates: As this is a graduate level course, it does not fulfill the Mathematical Thinking Liberal Education requirement. If you would like to take a statistics course in our department that fulfills that requirement, please consider EPSY 3264.