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MKTG Bayesian Inference: Methods and Applications

Intellectual Property: Life Sciences/ Biotechnology

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MKTG 646

Bayesian Inference: Methods and Applications

Graduate School of Business

Recommended for route(s):

[ Academia ] [ Regulatory & Policy ] Intellectual Property: Life Sciences/ Biotechnology

Why it is relevant for ...

[ Academia ] [ Regulatory & Policy ] as a Related Elective for those interested in Statistics : Drawing an inference from quantitative evidence lies at the heart of many legal and policy decisions and can be key to an academic's scholarly work. Students should consider taking one or more classes on statistics and statistical inference. This course examines econometrics from a Bayesian perspective, giving some attention to the foundations of Bayesian methodology.

General course Description:

The course aims to develop a thorough understanding of Bayesian inference, with a special focus on empirical applications in marketing. The course will start with a brief theoretical foundation to Bayesian inference and will subsequently focus on empirical methods. Initial topics would include Bayesian linear regression, multivariate regression, importance sampling and its applications. Subsequently, the course will focus on Markov Chain Monte Carlo (MCMC) methods including the Gibbs Sampler and the Metropolis-Hastings algorithm and their applications. The overall focus of the course will be on applying these methods for empirical research using a programming language such as R.

Course Style: A Substantive course teaches the law, theory, and policy in a particular area of law

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