Classical probability #
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The classical formulation of probability states that the probability of an event occurring in a
finite probability space is the ratio of that event to all possible events.
This notion can be expressed with measure theory using
the counting measure. In particular, given the sets s
and t
, we define the probability of t
occuring in s
to be |s|⁻¹ * |s ∩ t|
. With this definition, we recover the the probability over
the entire sample space when s = set.univ
.
Classical probability is often used in combinatorics and we prove some useful lemmas in this file for that purpose.
Main definition #
probability_theory.cond_count
: given a sets
,cond_count s
is the counting measure conditioned ons
. This is a probability measure whens
is finite and nonempty.
Notes #
The original aim of this file is to provide a measure theoretic method of describing the
probability an element of a set s
satisfies some predicate P
. Our current formulation still
allow us to describe this by abusing the definitional equality of sets and predicates by simply
writing cond_count s P
. We should avoid this however as none of the lemmas are written for
predicates.
Given a set s
, cond_count s
is the counting measure conditioned on s
. In particular,
cond_count s t
is the proportion of s
that is contained in t
.
This is a probability measure when s
is finite and nonempty and is given by
probability_theory.cond_count_is_probability_measure
.
A version of the law of total probability for counting probabilites.