Count data modelling comprises a suite of statistical techniques dedicated to analysing non-negative integer-valued observations. Such data often arise in a variety of contexts including epidemiology, ...

In this course, you will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to performing statistical hypothesis testing.

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 65, No. 3 (APRIL 2016), pp. 395-414 (20 pages) Motivated by an imaging study, the paper develops a non-parametric testing ...

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 paper presents semiparametric identification results for the Rust (1994) class of discrete choice dynamic programming (DCDP) models. We develop sufficient conditions for identification of the ...