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Baysian updating

Over the next several weeks, we will together explore Bayesian statistics.

In this module, we will work with conditional probabilities, which is the probability of event B given event A.

The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.

Even after centuries later, the importance of ‘Bayesian Statistics’ hasn’t faded away.

In fact, today this topic is being taught in great depths in some of the world’s leading universities.

Please read the background information, review the report template (downloaded from the link in Lesson Project Information), and then complete the peer review assignment.

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge.

You should check out this course to get a comprehensive low down on statistics and probability.

In several situations, it does not help us solve business problems, even though there is data involved in these problems.

To say the least, In 1770s, Thomas Bayes introduced ‘Bayes Theorem’.

By the end of this week, you will be able to implement Bayesian model averaging, interpret Bayesian multiple linear regression and understand its relationship to the frequentist linear regression approach.

In this module you will use the data set provided to complete and report on a data analysis question.

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By the end of this article, you will have a concrete understanding of Bayesian Statistics and its associated concepts. Therefore, it is important to understand the difference between the two and how does there exists a thin line of demarcation!

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