Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the ...

With humor and an engaging conversational style, he walks the reader through the basics of statistical concepts and their applications, using real-world examples to illustrate how statistics work ...

During his Ph.D. research, mathematician Tyron Lardy worked on a new approach to hypothesis testing. Instead of the traditional p-value, he uses so-called e-values. These turn out to be more ...

Statistical and Data Sciences Minor Requirements. Six courses plus SDS 100. SDS 100; Four foundation and core courses: CSC 110 or CSC 120; SDS 192; SDS 220 or SDS 201; SDS 291; One programming depth ...

A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and ...

Numerous examples from clinical research are worked through both manually and using SAS. Methods presented include t-tests, analysis of variance, repeated measures ANOVA, linear regression, analysis ...

The Durbin Watson (DW) statistic is a test for autocorrelation in the residuals from a statistical model or regression analysis. The Durbin-Watson statistic will always have a value ranging ...

Specialization: Data Science Foundations: Statistical Inference Instructor: Dr. Jem Corcoran, Associate Professor in Applied Mathematics Prior knowledge needed: Probability Theory: Foundation for Data ...