Bayesian Statistics Certification Course Part 1 : From Concept to Data Analysis

Bayesian Statistics Certification Course Part 1 : From Concept to Data Analysis ranks 7th in the list of best online probability & statistics courses. The Bayesian approach to statistics is introduced in this course, beginning with the concept of probability and progressing to data analysis. You will learn about the Bayesian approach's philosophy as well as how to apply it to common types of data. You will compare the Bayesian approach to the more commonly taught Frequentist approach and discuss some of its advantages. The Bayesian approach, in particular, allows for better accounting of uncertainty, results with more intuitive and interpretable meaning, and more explicit statements of assumptions. To create an active learning experience, this course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards.

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.

Skills you will gain:

• Statistics, Bayesian Statistics, Bayesian Inference, R Programming

Specifically you will learn about:

• Probability and Bayes’ Theorem
• Statistical Inference
  
• Priors and Models for Discrete Data
• Models for Continuous Data

Rating: 4.6/5.0

Enroll here: coursera.org/learn/bayesian-statistics