MATH 504 Modern Computational Statistics

4 semester hours

Generalized linear models: logistic, multinomial, and Poisson regression; bootstrapping: resampling simulations, estimation, confidence sets, and hypothesis testing; Bayesian methods: computational techniques such as Markov Chain Monte Carlo and Metropolis-Hastings, estimation, credible sets, and hypothesis testing.

Prerequisites: MATH 304 and MATH 361.

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