User Manual
6-57
Distribution
Inverse Cumulative Distribution
Normal
Distribution
p = p(x)dx
Upper
–∞
∫
p = p(x)dx
Lower
∞
∫
p = p(x)dx
Upper
Lower
∫
tail = Left tail = Right tail = Central
Student-
t
Distribution
p = p(x)dx
Lower
∞
∫
χ
2
Distribution
F Distribution
k Distribution (Discrete)
Distribution Probability
Binomial Distribution
p(x) =
nCxp
x
(1–p)
n – x
(x = 0, 1, ·······, n)
n : number of trials
Poisson Distribution
(x = 0, 1, 2, ···)
p(x) =
x!
e
–
μ
μ
×
x
μ
: mean (
μ
> 0)
Geometric Distribution
p(x)
= p(1– p)
x – 1
(x = 1, 2, 3, ···)
Hypergeometric
Distribution
p(x) =
MCx × N – MCn – x
N
Cn
n : Number of elements extracted from population (0 x integer)
M : Number of elements contained in attribute A (0 M integer)
N : Number of population elements ( n N , M N integer)
Distribution
Cumulative Distribution
Inverse Cumulative Distribution
Binomial Distribution
p =
Σ
p(x)
x=0
X
p H
Σ
p(x)
x=0
X
Poisson Distribution
Geometric Distribution
p =
Σ
p(x)
x=1
X
p H
Σ
p(x)
x=1
X
Hypergeometric
Distribution
p =
Σ
p(x)
x=0
X
p H
Σ
p(x)
x=0
X