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Basics of Non_Bayesian Regression Analysis

From Model Development to Model Comparison
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Content

Platform: Udemy
Video: 3h 48m
Language: English
Next start: On Demand

Table of contents

Description

This course is part one , of the series that starts with the fundamentals of the regression analysis , continues with Bayesian methods using the STAN probabilistic language , at the fourth course you can apply all the thins that you have learned in the first three courses in order to predict the Brain volume reduction , Brain Atrophy , after the age of 60 in the fully Bayesian Hierarchical Model with patients who have Alzheimer`s disease.
These courses enables you to adopt full Bayesian methods either in your research or practice and to write STAN probabilistic language  in single level of multilevel ( Hierarchical) Bayesian methodology.

You will learn

✓ Regression Analysis with R

Requirements

• Nothing ! Just curiosity about the method

This course is for

• Beginners
Mathematician / Physicist
I am graduate student in Applied Mathematics at York university , Toronto , Ontario , Canada. Previously , I had done another graduate degree in Theoretical Particle Physics which after that I joined a research team at the Montreal Neurological Institute and did research on Alzheimer`s disease and application of the AI in the diagnosis of the disorder before the initial symptoms of the dementia from the PET scans.Currently , I do both conduct a research on the application of the AI in the early diagnosis of cancer from the scattering coefficients of the lasers from the cancerous tissues.and also , I do teach mathematics and Physics at a college which recently I won the Canadian Meritorious Award for advising a team to win the first place at the 5th Annual Mathematical Modelling Challenge 2020.  I do like reading philosophical text books , then when I am not busy with research or teaching , I do spend my time reading books in a coffee shop.
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Platform: Udemy
Video: 3h 48m
Language: English
Next start: On Demand

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