Matrix-covariate is now frequently encountered in many biomedical researches. It is common to fit conventional statistical models by vectorizing matrix-covariate. This strategy results in a large ...

Statistical significance is a critical concept in data analysis and research. In essence, it’s a measure that allows researchers to assess whether the results of an experiment or study are due to ...

In the presence of covariate measurement error, there has been extensive interest in developing estimation methods for parameters associated with various survival ...

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 the realm of technical product development, hypothesis testing acts as a bridge between design, data and decision-making. It enables teams to move beyond assumptions and validate their ideas ...

Develop interdisciplinary skills in data science and gain knowledge of statistical analysis, data mining, and machine learning from one of the nation’s top-ranked Tier 1 research institutions. Earn ...

In the middle of the 20 th century, the field of psychology had a problem. In the wake of the Manhattan Project and in the early days of the space race, the so-called “hard sciences” were producing ...