This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

This comprehensive course bridges the gap between foundational statistical reasoning and practical applications related to business and engineering decision-making. Throughout the course, we’ll ...

Introduction to the Bayesian paradigm. Markov Chain Monte Carlo estimation using WinBUGS. Comparison with frequentist statistics. Noninformative and improper priors. Inference and model selection.

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

The purpose of the course is to introduce the statistical methods that are critical in the performance analysis and selection of information systems and networks. It includes fundamental topics as ...

An introduction to statistics in an agricultural and horticultural context, including the presentation, analysis and interpretation of quantitative data. The fourth number of the course code shows the ...

This course aims to introduce participants to the methodology of systematic reviews and meta-analysis. It is taught by a team of systematic reviewers, research synthesis methodologists, information ...