Measurement error models address the deviation between observed and true values, thereby refining the reliability of statistical inference. These frameworks are ...

Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results? I suggest that a philosophy compatible with statistical practice ...

Bayesian statistics have made great strides in recent years, developing a class of methods for estimation and inference via stochastic simulation known as Markov Chain Monte Carlo (MCMC) methods. MCMC ...

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 ...

In recent years, a need for compact representations of databases has become apparent, for example in natural language understanding, machine learning, and decision making, accompanied by a need for ...