Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Here's a statistical challenge worthy of a grandmaster: How do you create an accurate ranking system when the best players ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google is expanding its AI model family while addressing some of the ...

Count data modelling occupies a central role in statistical applications across diverse disciplines including epidemiology, econometrics and engineering. Traditionally, the Poisson distribution has ...

Statistics influence nearly everything. That is, the information and context derived from statistical analysis help to shape important decisions that have local, national, and global impacts. For ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 46, No. 3 (September/septembre 2018), pp. 399-415 (17 pages) For sparse and high-dimensional data analysis, a valid ...

Step into a career in the high-demand field of data science with a Master of Science from the University of Colorado Boulder. Our two-year, interdisciplinary program will prepare you to become a data ...

How to use statistical tools for component tolerance analysis. A look at methods such as Monte Carlo and Gaussian distribution. Simulating a dc-dc converter in LTspice to model closed-loop voltage ...