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 ...

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 ...

Bootstrap methods form a class of non‐parametric resampling techniques used to assess the variability and distributional properties of statistical estimators. By repeatedly drawing samples with ...

Selective inference addresses the problem of drawing valid conclusions after a data-driven selection of models or features. Traditional inferential procedures assume that the model under consideration ...

DTSA 5001 Probability and Foundations for Data Science and AI - Same as APPA 5001 DTSA 5002 Statistical Estimation for Data Science and AI - Same as APPA 5003 DTSA 5003 Statistical Inference and ...