The course provides a comprehensive coverage of fundamental aspects of methods and principles in probability and statistics, as well as linear regression analysis. Real data illustrations with the ...

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

This innovative method, known as hybrid Bayesian inference, blends different statistical approaches to better understand complex diseases like idiopathic pulmonary fibrosis, which has long puzzled ...

Statistics is a branch of math that involves the collection, description, analysis, and inference of conclusions from quantitative data. But what is a statistic? Let’s find out. The word ...

This paper reviews methodological issues if non-probability data are used to compile official statistics. Two different research lines can be identified to use non-probabilty data sources in the ...

Classical statistical inference methods: probability distribution estimation, confidence intervals for statistical results, hypothesis testing for statistical significance. Fitting of data using ...

More information: Daniel R. Kowal et al, Monte Carlo Inference for Semiparametric Bayesian Regression, Journal of the American Statistical Association (2024). DOI: 10.1080/01621459.2024.2395586 ...