Bayesian Statistics Using R
Master Bayesian statistical methods and practical implementation in R for data analysis and statistical modeling.
Master Bayesian statistical methods and practical implementation in R for data analysis and statistical modeling.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Bayesian Statistics Using R program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Understand Bayes' Theorem and differences between frequentist and Bayesian inference
Apply posterior inference techniques including credible intervals and posterior probabilities
Implement conjugate models such as gamma-poisson, beta-binomial, and normal models
Conduct Bayesian regression analysis and ANOVA
Use simulations and MCMC methods for posterior inference in R
Perform Bayesian cluster analysis and model comparison
Skills you'll gain
This course includes:
7.5 Hours PreRecorded video
Access on Mobile, Tablet, Desktop
FullTime access
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There are 2 courses in this program
Stepping Up: Preparing Yourself for Leadership
Course 1 · 18 Hours to complete · 4 modules
Industry 4.0: PLM, Value Chain, and Smart Factory
Course 2 · 7 Hours to complete · 3 modules
Fee Structure
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