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Published by: Massachusetts Institute of Technology | Language: English
Published by: Massachusetts Institute of Technology | Language: English
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This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality
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Tag(s):
- mathematics
- probability spaces
- random variables
- distribution functions
- binomial
- geometric
- hypergeometric
- poisson distributions
- uniform
- exponential
- normal
- gamma and beta distributions
- conditional probability
- bayes theorem
- joint distributions
- chebyshev inequality
- law of large numbers
- and central limit theorem
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Description:This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality
-
Description:This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality
-
Description:This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality
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