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Apr 20, 2024
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PSY 6115 - Introduction to Bayesian Data Analysis
An introduction to Bayesian data analysis focused on the application of Bayesian techniques to social science data. Major topics include the fundamentals of Bayesian inference, including the use of Markov Chain Monte Carlo computational techniques, and the application of Bayesian methods to data that otherwise would have been analyzed using the traditional statistical techniques taught in most standard introductory statistics textbooks.
Requisites: PSY 6112
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Students will be able to explain the basic ideas underlying Bayesian statistical inference
- Students will be able to explain the basic ideas underlying the estimation of posterior distributions in Bayesian statistical inference, including the use of Markov Chain Monte Carlo computational techniques
- Students will be able to compare and contrast Bayesian and frequentist approaches to statistical inference
- Students will be able to conduct a Bayesian analysis using statistical software for a wide range of data ranging from one-sample models to linear regression models
- Students will be able to prepare written reports of Bayesian analyses that are suitable for a professional journal
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