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Listen "Episode 12: Bayesian Fire Engine"
Episode Synopsis
In this episode, I tackled ‘omics’ data with a Bayesian fire engine, soared over a timeline of statistical ideas, and decreased statistical bias by increasing bias understanding.
References:
A Survey of Statistical Methods for Microbiome Data Analysis
PyCon US: Successful Return to In-Person in 2022
PUSH, POP, and reset options for ODS graphics
Using Bayesian Additive Regression Trees for Flexible Outcome Modeling
R 4.2.1 scheduled for June 23
Bias in Statistics: Definition, Selection Bias & Survivorship Bias
X-MR (X-Moving Range) Chart
From Anna Menacher: A timeline of the most important statistical ideas of the past 50 years
useR! 2022 – all virtual – is next week!
R-packages:
bnClustOmics: Bayesian Network-Based Clustering of Multi-Omics Data
starticles: A Generic, Publisher-Independent Template for Writing Scientific Documents in 'rmarkdown'
References:
A Survey of Statistical Methods for Microbiome Data Analysis
PyCon US: Successful Return to In-Person in 2022
PUSH, POP, and reset options for ODS graphics
Using Bayesian Additive Regression Trees for Flexible Outcome Modeling
R 4.2.1 scheduled for June 23
Bias in Statistics: Definition, Selection Bias & Survivorship Bias
X-MR (X-Moving Range) Chart
From Anna Menacher: A timeline of the most important statistical ideas of the past 50 years
useR! 2022 – all virtual – is next week!
R-packages:
bnClustOmics: Bayesian Network-Based Clustering of Multi-Omics Data
starticles: A Generic, Publisher-Independent Template for Writing Scientific Documents in 'rmarkdown'
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