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 ...

Bayesian estimation methods form a dynamic branch of statistical inference, utilising Bayes’ theorem to update probabilities in light of new evidence. This framework combines prior knowledge with ...

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 ...

On September 27th, 2024, the Department of Mathematics and Statistics at Concordia University proudly hosted the 11th installment of the Professor T.D. Dwivedi Memorial Lecture series. This annual ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

This course is available on the MPhil/PhD in International Relations and MRes/PhD in International Development. This course is available with permission as an outside option to students on other ...