This syllabus contains all relevant information about the course: description, grading criteria, schedules of course materials and weekly assignments and due dates. Consider this your roadmap for the ...

Statistical environments such as S, R, XLisp-Stat, and others have had a dramatic effect on the way we, statistics practitioners, think about data and statistical methodology. However, the ...

In today's data-driven world, statistical analysis plays a critical role in uncovering insights, validating hypotheses, and driving decision-making across industries. R, a powerful programming ...

R is a powerful open source programming environment primarily known for its statistical capabilities. In this course we will cover some advanced applications of R: distributed computing using the ...

Before you start analyzing, you might want to take a look at your data object’s structure and a few row entries. If it’s a 2-dimensional table of data stored in an R data frame object with rows and ...

This article reviews and interprets recent mathematics of special functions, with emphasis on integral representations of multiple hypergeometric functions. B.C. Carlson's centrally important ...

Although there are many commercially available statistical software packages, only a few implement a competing risk analysis or a proportional hazards regression model with time-dependent covariates, ...

1 Introduction: Consequences of Numerical Inaccuracy 1 -- 1.1 Importance of Understanding Computational Statistics 1 -- 1.2 Brief History: Duhem to the Twenty-First Century 3 -- 1.3 Motivating Example ...