# Bayesianism

## 0.1 Introduction

Instance of:

AKA:

Distinct from:

English:

Formalization:

The posterior, $$P(H|E)$$, is our final credibility over possible states of the world given the evidence we’ve observed. Our prior, $$P(H)$$, is the starting credibility we assigned to those states. The marginal, $$P(E)$$, is the probability of observing the evidence on average across all the possible states. The likelihood, P(E|H), is the probability of observing that evidence given a particular state of the world is true.

$P(H|E) = P(H) \times \frac{P(E|H)}{P(E)}$

Cites: Wikipedia ; Wikidata ; Wolfram

Code

Examples:

Examples:

library(DBI)
# Create an ephemeral in-memory RSQLite database
#con <- dbConnect(RSQLite::SQLite(), dbname = ":memory:")
#dbListTables(con)
#dbWriteTable(con, "mtcars", mtcars)
#dbListTables(con)

#* deb: libpq-dev libssl-dev (Debian, Ubuntu, etc)
#install.packages('RPostgres')
#remotes::install_github("r-dbi/RPostgres")
#Took forever because my file permissions were broken
#pg_lsclusters
require(RPostgres)
Loading required package: RPostgres
# Connect to the default postgres database
#I had to follow these instructions and create both a username and database that matched my ubuntu name
#https://www.digitalocean.com/community/tutorials/how-to-install-postgresql-on-ubuntu-20-04-quickstart
con <- dbConnect(RPostgres::Postgres())
import torch

## 0.2 Bayesian

English: Formalization:



Cites:

Code