Causal inference is important in medical research to help determine if treatments are beneficial and if natural exposures are harmful. In many settings, data collection makes causal inference ...

Length-biased and censored data arise when the probability of observing an event depends on its unobserved duration and when part of the observational history is unobserved due to study termination or ...

This online data science specialization is designed to provide you with a solid foundation in probability theory in preparation for the broader study of statistics. The specialization also introduces ...

Conditional independence testing seeks to determine whether two random variables are independent given the value of a third. This concept underpins causal discovery, graphical modelling and variable ...

Successful completion of this course demonstrate your achievement of the following learning outcomes for the MS-DS program: Define a composite hypothesis and the level of significance for a test with ...