Clemson University, Clemson, SC, USA      Spring 2020

Industrial Applications of Probability and Statistics (required undergraduate course) - 40 Students

• Introduces the central concept that overall system performance can be improved by taking uncertainty into account, especially through the reduction of variability. Specific industrial applications, such as decision analysis, reliability, and probabilistic inventory models, are emphasized.

• Topics include random experiments and combinatorics, axiomatic probability, conditional probability, independence, random variables, mathematical expectation and higher moments, discrete and continuous distributions, joint and conditional distributions, inequalities, and important limit theorems.

• Due to Covid-19 pandemic, second half of this course was online.

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