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We reviewed 3 live results for bayesian modeling and narrowed them down to the 3 options that look most worth comparing first.
The options are Bayesian Statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling and Business modeling.
Source: Duke University
Description
Bayesian Statistics is an online, self-paced course offered by Duke University's Department of Statistical Science as part of the Statistics with R Coursera Specialization. The course covers Bayesian inference, transforming prior probabilities into posterior probabilities with Bayes' rule, and practical modeling. Learners explore end-to-end analyses in R, credible regions, comparisons of means and proportions, Bayesian regression, multi-model inference, and prediction under the instruction of Duke faculty including Mine Çetinkaya-Rundel, David Banks, Colin Rundel, and Merlise Clyde.
Best for
data analysts, statisticians, learning Bayesian statistical modeling and implementing Bayesian inference in R
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Source: Routledge
Description
Bayes Rules!: An Introduction to Applied Bayesian Modeling by Alicia A. Johnson, Miles Q. Ott, and Mine Dogucu is a textbook published by Chapman & Hall. Designed for advanced undergraduate statistics students and practitioners, this 544-page introductory guide covers Bayesian thinking, conjugate families, Markov chain Monte Carlo simulation, regression, and hierarchical modeling with integrated R code, RStan tools, and the bayesrules package.
Best for
Advanced undergraduate statistics students, Data science practitioners, Introductory undergraduate Bayesian statistics courses and Self-study in applied Bayesian modeling and computation
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Source: LeitnerLeitner Slovakia
Description
Business modeling services by LeitnerLeitner Slovakia provide resilient business plans, integrated budgets, and long-term financial modeling to support decision-making for companies, lenders, and investors. The service encompasses planning, budgeting, forecasting, target/actual comparisons, financial model development, audits, reviews, business reporting, and target group-oriented financial presentations. Drawing on cross-disciplinary collaboration across accounting, audit, and tax fields, the team assists corporate clients, family businesses, and private individuals with investment projects, restructuring processes, transactions, and strategic management.
Best for
companies, lenders, investment projects and restructuring processes
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| Compare | #1Bayesian Statistics | #2Bayes Rules!: An Introduction to Applied Bayesian Modeling | #3Business modeling |
|---|---|---|---|
| Source | Duke University | Routledge | LeitnerLeitner Slovakia |
| Description | Bayesian Statistics is an online, self-paced course offered by Duke University's Department of Statistical Science as part of the Statistics with R Coursera Specialization. The course covers Bayesian inference, transforming prior probabilities into posterior probabilities with Bayes' rule, and practical modeling. Learners explore end-to-end analyses in R, credible regions, comparisons of means and proportions, Bayesian regression, multi-model inference, and prediction under the instruction of Duke faculty including Mine Çetinkaya-Rundel, David Banks, Colin Rundel, and Merlise Clyde. | Bayes Rules!: An Introduction to Applied Bayesian Modeling by Alicia A. Johnson, Miles Q. Ott, and Mine Dogucu is a textbook published by Chapman & Hall. Designed for advanced undergraduate statistics students and practitioners, this 544-page introductory guide covers Bayesian thinking, conjugate families, Markov chain Monte Carlo simulation, regression, and hierarchical modeling with integrated R code, RStan tools, and the bayesrules package. | Business modeling services by LeitnerLeitner Slovakia provide resilient business plans, integrated budgets, and long-term financial modeling to support decision-making for companies, lenders, and investors. The service encompasses planning, budgeting, forecasting, target/actual comparisons, financial model development, audits, reviews, business reporting, and target group-oriented financial presentations. Drawing on cross-disciplinary collaboration across accounting, audit, and tax fields, the team assists corporate clients, family businesses, and private individuals with investment projects, restructuring processes, transactions, and strategic management. |
| Best for | data analysts, statisticians, learning Bayesian statistical modeling and implementing Bayesian inference in R | Advanced undergraduate statistics students, Data science practitioners, Introductory undergraduate Bayesian statistics courses and Self-study in applied Bayesian modeling and computation | companies, lenders, investment projects and restructuring processes |
| Action | Duke University | Routledge | LeitnerLeitner Slovakia |
| Rate this product |
"Bayesian Statistics from Duke University."
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