Sample space, Field and Probability Measure. Axiomatic definition of Probability. Bayes' theorem. Repeated trials. Continuous and discrete random variables and their probability distribution and ...

Provides a one-semester course in probability and statistics with applications in the engineering sciences. Probability of events, discrete and continuous random variables cumulative distribution, ...

We’ll learn what it means to calculate a probability, independent and dependent outcomes, and conditional events. We’ll study discrete and continuous random variables and see how this fits with data ...

Additionally, students must always refer to course syllabus for the most up to date information. Introduces students to the tools methods and theory behind extracting insights from data. Covers ...

Introduction to probability theory and statistical methods necessary for analyzing the behavior of processes and experiments. Statistical tests for detecting significant changes in process parameters.

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 ...

Equivalent combinations may be accepted at the lecturer’s discretion. The course covers the probability and distribution theory needed for advanced courses in statistics and econometrics.: Topics ...

Stanford University offers 5 free online courses in engineering. Courses include IoT, Probability Management, and Quantum Mechanics and the duration of these courses is 60 days.

This course is available with permission to General Course students. This is a first course in measure-theoretic probability. It covers the following topics. Abstract probability spaces: sample spaces ...