Theorem. E(X) = np If X has a Binomial distribution, then Var(X) = npq mx(t) = (pe¹ + q)

College Algebra (MindTap Course List)
12th Edition
ISBN:9781305652231
Author:R. David Gustafson, Jeff Hughes
Publisher:R. David Gustafson, Jeff Hughes
Chapter8: Sequences, Series, And Probability
Section8.7: Probability
Problem 39E: Assume that the probability that an airplane engine will fail during a torture test is 12and that...
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Provide the proof

Binomial Distribution
Definition:
Theorem.
E(X) = np
Proof:
A random variable X is defined to have a binomial distribution,
denoted by X-Bi(n,p), if the PMF of X is given by:
Px(x) =
n
(*) ₁² (1-P)
n-x
{0,1,2,...} (x)
where the two parameters n and p satisfy 0 ≤ p ≤ 1, n ranges
over the positive integers. (1-p) is often denoted by q.
If X has a Binomial distribution, then
Var(X) = npq
mx(t) = (pe¹ + q)n
Transcribed Image Text:Binomial Distribution Definition: Theorem. E(X) = np Proof: A random variable X is defined to have a binomial distribution, denoted by X-Bi(n,p), if the PMF of X is given by: Px(x) = n (*) ₁² (1-P) n-x {0,1,2,...} (x) where the two parameters n and p satisfy 0 ≤ p ≤ 1, n ranges over the positive integers. (1-p) is often denoted by q. If X has a Binomial distribution, then Var(X) = npq mx(t) = (pe¹ + q)n
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