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[su_tab title = “Description”]
After taking this online course, you will be able to install and run rjags, a program for Bayesian analysis within R. Using R and rjags, you will learn how to specify and run Bayesian modeling procedures using regression models for continuous, count and categorical data. Procedures covered from a Bayesian perspective include linear regression, Poisson, logit and negative binomial regression, and ordinal regression.
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[su_tab title = “Program Structure”]
Course Program:
- Week 1: Using rjags for Bayesian inference in R: Introductory Ideas and Programming Considerations
- Week 2: Linear Regression with rjags
- Week 3: Regression for Count, Binary and Binomial Data
- Week 4: Other Regression Techniques
Important Date:
March 25, 2016 to April 22, 2016
Duration:
4 Weeks
Time Requirement:
About 15 hours per week, at times of your choosing.
Fees:
INR 37,740 (assuming $ = INR 60)
Part Time/Full Time:
Part Time
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[su_tab title = “Eligibility”]
Pre-requisites:
You should take this course if you are familiar with R and with Bayesian statistics at the introductory level, and work with or interpret statistical models and need to incorporate Bayesian methods. Analysts who need to incorporate their work into real-world decisions, as opposed to formal statistical inference for publication, will be especially interested. This includes business analysts, environmental scientists, regulators, medical researchers, and engineers.
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[su_tab title =”Tools”]
- R
- JAGS
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[su_tab title = “Faculty”]
- Peter Congdon
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[su_tab title = “Contact”]
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