The binomial distribution

This file defines the probability mass function of the binomial distribution.

Main results

• binomial_one_eq_bernoulli: For n = 1, it is equal to PMF.bernoulli.

noncomputable def PMF.binomial (p : ENNReal) (h : p ≤ 1) (n : ℕ) : PMF (Fin (n + 1))

The binomial PMF: the probability of observing exactly i “heads” in a sequence of n independent coin tosses, each having probability p of coming up “heads”.

Equations

• PMF.binomial p h n = PMF.ofFintype (fun (i : Fin (n + 1)) => p ^ ↑i * (1 - p) ^ (↑(Fin.last n) - ↑i) * ↑(n.choose ↑i)) ⋯

theorem PMF.binomial_apply (p : ENNReal) (h : p ≤ 1) (n : ℕ) (i : Fin (n + 1)) : (PMF.binomial p h n) i = p ^ ↑i * (1 - p) ^ (↑(Fin.last n) - ↑i) * ↑(n.choose ↑i)

@[simp]

theorem PMF.binomial_apply_zero (p : ENNReal) (h : p ≤ 1) (n : ℕ) : (PMF.binomial p h n) 0 = (1 - p) ^ n

@[simp]

theorem PMF.binomial_apply_last (p : ENNReal) (h : p ≤ 1) (n : ℕ) : (PMF.binomial p h n) (Fin.last n) = p ^ n

theorem PMF.binomial_apply_self (p : ENNReal) (h : p ≤ 1) (n : ℕ) : (PMF.binomial p h n) ↑n = p ^ n

theorem PMF.binomial_one_eq_bernoulli (p : ENNReal) (h : p ≤ 1) : PMF.binomial p h 1 = PMF.map (fun (x : Bool) => bif x then 1 else 0) (PMF.bernoulli p h)

The binomial distribution on one coin is the bernoully distribution.