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Bayesian statistics

The Open University via OpenLearn

Description

This free course is an introduction to Bayesian statistics. Section 1 discusses several ways of estimating probabilities. Section 2 reviews ideas of conditional probabilities and introduces Bayes’ theorem and its use in updating beliefs about a proposition, when data are observed, or information becomes available. Section 3 introduces the main ideas of the Bayesian inference process. The prior distribution summarises beliefs about the value of a parameter before data are observed. The likelihood function summarises information about a parameter contained in observed data and the posterior distribution represents what is known about a parameter after the data have been observed.

Tags
Electrical Engineering Social Media Marketing

Syllabus

  • Introduction
  • Learning outcomes
  • Link to course PDF
  • Conclusion
  • Acknowledgements

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Bayesian statistics

The Open University
Start Learning Find study partner
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  • Type
    Online Courses
  • Provider
    OpenLearn

This free course is an introduction to Bayesian statistics. Section 1 discusses several ways of estimating probabilities. Section 2 reviews ideas of conditional probabilities and introduces Bayes’ theorem and its use in updating beliefs about a proposition, when data are observed, or information becomes available. Section 3 introduces the main ideas of the Bayesian inference process. The prior distribution summarises beliefs about the value of a parameter before data are observed. The likelihood function summarises information about a parameter contained in observed data and the posterior distribution represents what is known about a parameter after the data have been observed.

  • Introduction
  • Learning outcomes
  • Link to course PDF
  • Conclusion
  • Acknowledgements

Tags

Electrical Engineering Social Media Marketing

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