Fuzzy statistics and random variables represent a progressive fusion of traditional probability theory with the principles of fuzzy logic, enabling the treatment of imprecision and vagueness inherent ...

This course covers descriptive statistics, random variables and expected value, discrete and continuous probability distributions, joint distribution functions, sampling distributions, point and ...

This is a preview. Log in through your library . Abstract For each $k = 1, 2, \cdots$ let $n = n(k)$, let $m = m(k)$, and suppose $y_1^k, \cdots, y_n^k$ is an $m ...

If random variables in one set are defined as explicit functions of random variables in a second set, Taylor series expansion (the delta method) may be used to prove the asymptotic normality of the ...

This course builds a rigorous foundation of probability. Topics covered include: basic concepts of probability theory and statistics, counting, axioms of probability, independence, Bayes rule, ...

Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...

Basic statistical concepts presented with emphasis on their relevance to biological and medical investigations. Evaluation is through problem sets, quizzes embedded within asynchronous videos, use of ...