Motivated by applications to prediction and forecasting, we suggest methods for approximating the conditional distribution function of a random variable Y given a dependent random d-vector X. The idea ...

Possibility theory and conditional probability offer complementary perspectives for modelling uncertainty, with each framework contributing distinct advantages. Possibility theory, rooted in fuzzy set ...

Explain why probability is important to statistics and data science. See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance ...

Nonparametric maximum likelihood estimation of the probability of failing from a particular cause by time t in the presence of other acting causes (i.e., the cause-specific failure probability) is ...

How likely you think something is to happen depends on what you already believe about the circumstances. That is the simple ...

Probability theorem gets quantum makeoverWhat would Thomas Bayes think? In 1763, he proposed a new approach to calculate ...

This course is available on the BSc in Data Science, BSc in Mathematics with Data Science and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on ...