Continuous Variable: can take on any value between two specified values. Obtained by measuring. Covariance: a measure of the direction of the linear relationship between two variables. Discrete ...

This is a graduate-level course focused on techniques and models in modern discrete probability. Topics include: the first and second moment methods, Chernoff bounds and large deviations, martingales, ...

This is a graduate-level course focused on techniques and models in modern discrete probability. Topics include: the first and second moment methods, martingales, concentration inequalities, branching ...

Discrete gust models, although idealizations of actual atmospheric conditions, are useful for engineering design. For fatigue design, these models must be representative of the conditions a structure ...

Description: Basic set theory, elementary probability theory, discrete probability models, finite Markov chains. Applications to problems in the management and social sciences.

A nonparametric probability density estimator is proposed that is optimal with respect to a discretized form of a continuous penalized-likelihood criterion functional. Approximation results relating ...

This course provides a solid basis for further study in statistics and data analysis or in pattern recognition and operations research. It is especially appropriate for students with an undergraduate ...

The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Probabilistic modeling and the related field of statistical ...