Bayesian Statistics
About this course
This Specialization is intended for all learners seeking to develop proficiency in statistics, Bayesian statistics, Bayesian inference, R programming, and much more. Through four complete courses (From Concept to Data Analysis; Techniques and Models; Mixture Models; Time Series Analysis) and a culminating project, you will cover Bayesian methods — such as conjugate models, MCMC, mixture models, and dynamic linear modeling — which will provide you with the skills necessary to perform analysis, engage in forecasting, and create statistical models using real-world data.
82/100
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- What the provider tells you
- 31/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- develop proficiency in statistics
- understand Bayesian inference
- apply R programming for statistical analysis
- perform analysis and forecasting using Bayesian methods
Course objectives
- to teach Bayesian statistics concepts
- to provide practical experience through a culminating project
- to explore advanced statistical models and analysis techniques
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