Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness; tests of simple and composite hypotheses, linear models, and multiple regression ...

This is an introductory course on statistics and how it can help us answer the kind of questions that arise when we want to better understand the world. We will use real-world examples from the social ...

This course introduces students to statistics and quantitative information. The course surveys probability theory, hypothesis testing, descriptive statistics and visualizations, and inferential ...

This campus-based module is led by Stephen Walters. It runs in the Autumn semester and is worth 15 credits. This module introduces students to the basic concepts and techniques of medical statistics, ...