Bayesian Statistics and Credibility Theory
Bayesian Statistics and Credibility Theory, available at $29.99, has an average rating of 4.5, with 11 lectures, based on 88 reviews, and has 1739 subscribers.
You will learn about Bayesian Statistics and Credibility Theory This course is ideal for individuals who are Students wanting to writing the Actuarial Exams It is particularly useful for Students wanting to writing the Actuarial Exams.
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Summary
Title: Bayesian Statistics and Credibility Theory
Price: $29.99
Average Rating: 4.5
Number of Lectures: 11
Number of Published Lectures: 11
Number of Curriculum Items: 11
Number of Published Curriculum Objects: 11
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Bayesian Statistics and Credibility Theory
Who Should Attend
- Students wanting to writing the Actuarial Exams
Target Audiences
- Students wanting to writing the Actuarial Exams
This short course aims to address the following syllabus objectives of the Actuarial Exams:
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Explain the fundamental concepts of Bayesian statistics and use these concepts to calculate Bayesian estimators.
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Use Bayes’ theorem to calculate simple conditional probabilities.
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Explain what is meant by a prior distribution, a posterior distribution and a conjugate prior distribution.
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Derive the posterior distribution for a parameter in simple cases.
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Explain what is meant by a loss function.
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Use simple loss functions to derive Bayesian estimates of parameters.
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Explain what is meant by the credibility premium formula and describe the role played by the credibility factor.
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Explain the Bayesian approach to credibility theory and use it to derive credibility premiums in simple cases.
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Explain the empirical Bayes approach to credibility theory and use it to derive credibility premiums in simple cases.
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Explain the differences between the two approaches and state the assumptions underlying each of them.
Course Curriculum
Chapter 1: Bayesian Statistics and Credibility Theory
Lecture 1: Visual Recap of Conditional Probability
Lecture 2: Bayesian Statistics Example
Lecture 3: Prior and Posterior Distributions
Lecture 4: Notation
Lecture 5: Prior and Posterior Example
Lecture 6: Conjugate Priors
Lecture 7: Loss Functions
Lecture 8: Credibility Theory
Lecture 9: Bayesian Credibility
Lecture 10: Empirical Bayes Credibility Theory
Lecture 11: Exam Question on EBCT
Instructors
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Michael Jordan
Actuary (FASSA/CERA)
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 0 votes
- 3 stars: 17 votes
- 4 stars: 26 votes
- 5 stars: 43 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
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