This preview shows page 1. Sign up to view the full content.
P(BIA)=P(A and B)/P(A)
Probability of B given A
P(BIA) does not = P(AIB) if it does, they’re dependent
= !  !
nPr n n r
Use if ABC is different than CBA
= !  ! !
nCr n n r r
Use if ABC is the same as CBA
0!=1
Probability Distribution
Rules1.) sum of all probabilities=1 2.) each value is between 0 and 1 inclusive
µ=∑
x∙Px
mean
σ²=∑
[(  )
( )]
x µ ²∙P x
variance
σ²=∑
[
( )]
x²∙P x µ²
variance
σ=∑
[
( )]
x²∙P x µ²
standard deviation
Binomial Probability
Rules1.) procedure has a fixed number of trials, 2.) trials must be independent, 3.) results must be classified into 2
categoriessuccess/failure, 4.) probability of success remains the same for all trials
µ=np
p
=probability of success
x
=denotes specific #of successes in
n
trials (between 0 and
n
)
σ²=npq
q
=probability of failure
p
=probability of success in one of the
n
trials
σ=
npq
n
=number of trials
q
=probability of failure in one of the
n
trials
= !  ! !*
*

Px n n x x px qn x
This is the end of the preview. Sign up
to
access the rest of the document.
This note was uploaded on 04/17/2008 for the course MATH unknown taught by Professor Sapko during the Fall '08 term at Mass Colleges.
 Fall '08
 Sapko
 Statistics, Probability

Click to edit the document details