In this three-course specialization, you’ll build a strong mathematical foundation in probability, statistics, and basic stochastic processes with direct applications to data science and AI. You’ll ...

Stein's method has emerged as a powerful and versatile tool in probability theory for deriving error bounds in distributional approximations. Originally developed to ...

This comprehensive course bridges the gap between foundational statistical reasoning and practical applications related to business and engineering decision-making. Throughout the course, we’ll ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...

No matter the field, if a researcher is collecting data of any kind, at some point he is going to have to analyze it. And odds are he’ll turn to statistics to figure out what the data can tell him. As ...

Quick—if you had to guess, what would you think is most likely to end all life on Earth: a meteor strike, climate change or a solar flare? (Choose carefully.) A new statistical method could help ...