There's nothing to get a scientist's heart pumping like a good, old-fashioned statistical debate. When it comes to topics ...

A new reconstruction method is explored using Bayesian inference for Poisson Statistics for emission tomography. The Gamma density function is chosen as the natural choice for the activity ...

Bayes' Theorem shows that even if a person tested positive in this scenario, there is a 19.76% chance the person takes the drug and an 80.24% chance they don't.

The typical participant is a PhD student in Statistics or related fields (Mathematical Statistics, Engineering Science, Quantitative Finance, Computer Science, ...). The participants are expected to ...

While the majority of stroke researchers use frequentist statistics to analyze and present their data, Bayesian statistics are becoming more and more prevalent in stroke research. As opposed to ...

Zampieri FG, Casey JD, Shankar-Hari M, Harrell FE, Harhay MO. Using Bayesian methods to augment the interpretation of critical care trials. An overview of theory and example reanalysis of the alveolar ...

For example, a researcher may be interested in the conditional probability of developing cancer given a particular risk factor such as smoking. We extend this to Bayesian statistics and update beliefs ...

Developing a strong intuitive understanding of Bayesian statistics is crucial for students. Start by explaining the Bayes' theorem in simple terms, perhaps using visual aids like probability trees ...

In this article we will explore key differences between Bayesian and traditional frequentist statistical approaches, some fundamental concepts at the core of Bayesian statistics, the central Bayes’ ...

The resulting vector tends to a multi-dimensional Gaussian distribution, with the dimension equal to the number of bins. The examples studied here do not, however, have independent and identically ...