Classical probability #
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
occurring in s
to be |s|⁻¹ * |s ∩ t|
. With this definition, we recover 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 #
ProbabilityTheory.condCount
: given a sets
,condCount 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 condCount s P
. We should avoid this however as none of the lemmas are written for
predicates.
Given a set s
, condCount s
is the counting measure conditioned on s
. In particular,
condCount 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
ProbabilityTheory.condCount_isProbabilityMeasure
.
Equations
- ProbabilityTheory.condCount s = ProbabilityTheory.cond MeasureTheory.Measure.count s
Instances For
Equations
- ⋯ = ⋯
A version of the law of total probability for counting probabilities.