Duke University

Bayesian Statistics

Taught in English

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Mine Çetinkaya-Rundel
David Banks
Colin Rundel

Instructors: Mine Çetinkaya-Rundel

74,653 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

3.8

(791 reviews)

|

78%

Intermediate level
Some related experience required
34 hours (approximately)
Flexible schedule
Learn at your own pace

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

3.8

(791 reviews)

|

78%

Intermediate level
Some related experience required
34 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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This course is part of the Data Analysis with R Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 7 modules in this course

This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Bayesian Statistics. Please take several minutes read this information. Thanks for joining us in this course!

What's included

1 video4 readings1 discussion prompt

<p>Welcome! Over the next several weeks, we will together explore Bayesian statistics. <p>In this module, we will work with conditional probabilities, which is the probability of event B given event A. Conditional probabilities are very important in medical decisions. By the end of the week, you will be able to solve problems using Bayes' rule, and update prior probabilities.</p><p>Please use the learning objectives and practice quiz to help you learn about Bayes' Rule, and apply what you have learned in the lab and on the quiz.

What's included

9 videos4 readings3 quizzes

In this week, we will discuss the continuous version of Bayes' rule and show you how to use it in a conjugate family, and discuss credible intervals. By the end of this week, you will be able to understand and define the concepts of prior, likelihood, and posterior probability and identify how they relate to one another.

What's included

10 videos3 readings3 quizzes

In this module, we will discuss Bayesian decision making, hypothesis testing, and Bayesian testing. By the end of this week, you will be able to make optimal decisions based on Bayesian statistics and compare multiple hypotheses using Bayes Factors.

What's included

14 videos3 readings3 quizzes

This week, we will look at Bayesian linear regressions and model averaging, which allows you to make inferences and predictions using several models. 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.

What's included

11 videos3 readings3 quizzes

This week consists of interviews with statisticians on how they use Bayesian statistics in their work, as well as the final project in the course.

What's included

3 videos1 reading

In this module you will use the data set provided to complete and report on a data analysis question. Please read the background information, review the report template (downloaded from the link in Lesson Project Information), and then complete the peer review assignment.

What's included

1 reading1 peer review

Instructors

Instructor ratings
3.6 (52 ratings)
Mine Çetinkaya-Rundel
Duke University
8 Courses391,654 learners
David Banks
Duke University
2 Courses75,729 learners
Colin Rundel
Duke University
2 Courses75,729 learners

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Duke University

Recommended if you're interested in Data Analysis

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3.8

791 reviews

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RC
5

Reviewed on Mar 21, 2020

PA
4

Reviewed on Oct 12, 2018

TM
4

Reviewed on Mar 9, 2017

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