[09x03] Bayesian Linear Regression | Turing.jl | Weight and Height Association in Human Adults

In this Julia Probabilistic Programming tutorial, you'll see both a non-Bayesian approach and a Bayesian approach to solving a Linear Regression problem.
For the Bayesian approach, you'll use the Turing.jl package.
You'll also see how to make predictions using both a non-Bayesian approach as well as a Bayesian approach.
As a motivating example, we'll use the Howell dataset of human heights and weights.
00:00 Intro
00:40 Set-up
02:27 Data
06:05 Non-Bayesian Approach
09:44 Bayesian Approach
22:07 Compare and Contrast Non-Bayesian Approach versus Bayesian Approach
24:10 Outro
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Links for this tutorial
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data for this tutorial
url = "raw.githubusercontent.com/rmc..."
Code for this tutorial (GitHub)
github.com/julia4ta/tutorials...
McElreath, Richard. "Statistical Rethinking 2023 - 03 - Geocentric Models." 2023. (RUclips)
• Statistical Rethinking...
Grantham, Neal. "Statistical Rethinking homework solutions with Turing.jl." 2022.
www.nsgrantham.com/stat-rethi...
GLM.jl Documentation
juliastats.org/GLM.jl/stable/
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Links for this series
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Link to Series 9 Playlist [Julia Probabilistic Programming for Beginners]
• [09x01] How Much of Ea...
Turing.jl Documentation
turinglang.org/stable/docs/us...
Turing.jl (GitHub)
github.com/TuringLang/Turing.jl
Turing.jl Website
turinglang.org/stable/
StatsPlots.jl Documentation
docs.juliaplots.org/latest/ge...
StatsPlots.jl (GitHub)
github.com/JuliaPlots/StatsPl...
Distributions.jl Documentation
juliastats.org/Distributions....
Distributions.jl (GitHub)
github.com/JuliaStats/Distrib...
The Julia Programming Language
julialang.org/
docs.julialang.org/en/v1/
/ @thejulialanguage
VS Code
code.visualstudio.com/
Pluto.jl
plutojl.org/
github.com/fonsp/Pluto.jl
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/ @doggodotjl
Thank you!

[@doggodotjl]

Leaving a comment to feed the algorithm!

[@alperyldrm4788]

Thanks man! Great content, as always.

[@TalsBadKidney]

good dog

[@net_puti]

nice content, awesome wizard

[@doggodotjl]

Thanks for watching!

[@we-gold]

This reminds me of confidence intervals vs inference tests. The bayesian approach contains much more information, but could be used to find approximately the same result if desired. Anyway, nice series!

[@doggodotjl]

It's always nice to have more tools in the toolkit!

[@CaribouDataScience]

What about predicting gender?

[@doggodotjl]

Good question. I'm not sure how to use height & weight data to predict gender, since there's so much data overlap. It is possible to created a Bayesian Logistic Regression model using height as the causal factor to predict gender. I cover Bayesian Logistic Regression in the next tutorial. I'd be curious to know your thoughts. Do you have any suggestions?