6-55
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
C
2
Distribution
F
Distribution
I
Distribution (Discrete)
Distribution
Probability
Binomial Distribution
p
(
x
)
=
n
C
x
p
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
M
: mean (
M
0)
Geometric Distribution
p
(
x
)
=
p
(1–
p
)
x
– 1
(
x
= 1, 2, 3, ···)
Hypergeometric
Distribution
p
(
x
)
=
M
C
x
×
N
–
M
C
n
–
x
N
C
n
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
=
p
(
x
)
x
=
0
X
p
H
p
(
x
)
x
=
0
X
Poisson Distribution
Geometric Distribution
p
=
p
(
x
)
x
=
1
X
p
H
p
(
x
)
x
=
1
X
Hypergeometric
Distribution
p
=
p
(
x
)
x
=
0
X
p
H
p
(
x
)
x
=
0
X
Содержание FX-7400GII
Страница 337: ...E CON2 Application ...
