Going back to teaching, hurray!

Hello everbody and it is good to be back after a nice and cozy Easter break. As probably most of you, I was too forced to spend my Easter holidays away from my family this year but at least here in the Netherlands the weather was pretty nice during the Easter weekend and I was able to enjoy a nice walk through the city center of Maastricht which was an amazing experience.

Sunny days which I cannot fully enjoy

Here we are again. Except now it feels like a very nice spring time here in Maastricht with beautiful sunny days an warm weather. The picture does not really represent the environment in this region of the Netherlands (called Limburg), but I thought it was a very nice picture to put as thumbnail.

Doing some teaching...

Hello everybody, it is time for some quick updates about myself and what I have been doing the past month. Well, essentially, I have been crazy busy doing lots of teaching on statistics-related subjects, which is the primary reason I was hired here in Maastricth.

What is a Bayesian credible interval

Happy new year everybody! Yeah, I know it already almost February but I have been incredibly busy the past few weeks after the Xmas break. From getting familiar with the courses I am teaching this term to providing consultancy advice on statistical problems for students from FHML at UM.

What is Bayesian inference?

What is probability ? The answer to this question is generally acknowledged to be the one that respects the so called Kolmogorov axioms which can be brutally simplified to:

Why be Bayesian?

Many times I have been asked by co-workers and people around me who are a bit familiar with statistics why I choose to be Bayesian and whether I feel confident in using this approach for my data analysis rather than the most widely accepted frequentist methods, at least in my research area.

The P value fallacy

Today, I would like to briefly comment an interesting research article written by Goodman, who provided a clear and exemplary discussion about the typical incorrect interpretation of a standard frequentist analysis in the field of medical research.