Bayesian Statistics: Techniques and Models

Description

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our ?Bayesian toolbox? with more general models, and computational techniques to fit them. In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. We will use the open-source, freely available software R (some experience is assumed, e.g., completing the previous course in R) and JAGS (no experience required). We will learn how to construct, fit, assess, and compare Bayesian statistical models to answer scientific questions involving continuous, binary, and count data. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. The lectures provide some of the basic mathematical development, explanations of the statistical modeling process, and a few basic modeling techniques commonly used by statisticians. Computer demonstrations provide concrete, practical walkthroughs. Completion of this course will give you access to a wide range of Bayesian analytical tools, customizable to your data.

Read more.

Career Relevance by Data Role

The techniques and tools covered in Bayesian Statistics: Techniques and Models are most similar to the requirements found in Data Scientist job advertisements.


Similarity Scores (Out of 100)

Subscribe for updates and new courses
Or create a DataKwery.com account
Fast Facts

Tools
R

Techniques
Bayesian StatisticsData AnalysisData ModelingDistributionsMonte Carlo SimulationsRegressionStatistical AnalysisUser Experience

Similar Opportunities
Bayesian Statistics: Mixture Models

Coursera - University of California, Santa Cruz

Bayesian Statistics: From Concept to Data Analysis

Coursera - University of California, Santa Cruz