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 ...

This is an introductory course in statistics. Topics that we will cover include elementary statistical measures, statistical distributions, statistical inference, hypothesis testing and linear ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Empirical likelihood methods have emerged as a robust, non‐parametric framework for statistical inference that skilfully bypasses the need for strong parametric assumptions. By constructing likelihood ...

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 ...

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 ...

Let’s start with a definition of Applied Statistics: Applied Statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an ...