This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach. In particular, the Bayesian approach allows for better accounting of uncertainty, results that have more intuitive and interpretable meaning, and more explicit statements of assumptions. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. For computing, you have the choice of using Microsoft Excel or the open-source, freely available statistical package R, with equivalent content for both options. The lectures provide some of the basic mathematical development as well as explanations of philosophy and interpretation. Completion of this course will give you an understanding of the concepts of the Bayesian approach, understanding the key differences between Bayesian and Frequentist approaches, and the ability to do basic data analyses.
Este curso forma parte de Programa especializado: Estadística bayesiana
Ofrecido Por
Programa especializado: Estadística bayesianaUniversidad de California en Santa CruzAcerca de este Curso
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Prueba Coursera para negociosHabilidades que obtendrás
- Statistics
- Bayesian Statistics
- Bayesian Inference
- R Programming
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Prueba Coursera para negocios
Ofrecido por
Programa - Qué aprenderás en este curso
Probability and Bayes' Theorem
Statistical Inference
Priors and Models for Discrete Data
Models for Continuous Data
Reseñas
- 5 stars66,95 %
- 4 stars25,45 %
- 3 stars5,29 %
- 2 stars1,34 %
- 1 star0,95 %
Principales reseñas sobre BAYESIAN STATISTICS: FROM CONCEPT TO DATA ANALYSIS
This is first time exposure to bayesian statistics and I must say it has given me a different perspective to analyzing data especially when dealing with unpredictable data or unknown data.
This is a good course for reviewing basic concepts of statistics, and good for starting learning Bayesian, as introduced as a basic course. If you want to learn deeper, go and find another course!
Very insightful. I'd recommend this course to anyone who wants to learn how to adjust a model after observing data. Test questions were quite practical modeling real world scenarios.
Very nice introduction to bayesian concepts and rationale. With this course I could understand why should I spend more time learning this technique (which I will definetly do on sequence).
Acerca de Programa especializado: Estadística bayesiana
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What are the pre-requisites for this course?
What computing resources are expected for this course?
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