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t
Inverse Student's
Cumulative Distribution .... [Inv. Distribution] - [Inverse
Calculates the lower bound value of a Student's
values.
χ χ
2
Probability Density .... [Distribution] - [χ
Calculates the χ
2
probability density for a specified value.
χ
2
Cumulative Distribution .... [Distribution] - [χ
Calculates the cumulative probability of a χ
bound and an upper bound.
Inverse χ
Cumulative Distribution .... [Inv. Distribution] - [Inverse χ
2
Calculates the lower bound value of a χ
F
Probability Density .... [Distribution] - [F PD]
F
Calculates the
probability density for a specified value.
F
Cumulative Distribution .... [Distribution] - [F CD]
Calculates the cumulative probability of an
between a lower bound and an upper bound.
F
Inverse
Cumulative Distribution .... [Inv. Distribution] - [Inverse F CD]
Calculates the lower bound value of an
Binomial Distribution Probability .... [Distribution] - [Binomial PD]
Calculates the probability in a binomial distribution that success will
occur on a specified trial.
Binomial Cumulative Distribution .... [Distribution] - [Binomial CD]
Calculates the cumulative probability in a binomial distribution that success will occur on or before a specified
trial.
Inverse Binomial Cumulative Distribution .... [Inv. Distribution] - [Inverse Binomial CD]
Calculates the minimum number of trials of a binomial cumulative probability distribution for
specified values.
Poisson Distribution Probability .... [Distribution] - [Poisson PD]
Calculates the probability in a Poisson distribution that success will occur on a specified trial.
0712
To calculate Poisson probability for the data below and graph the result
Specified trial: 10
t
cumulative probability distribution for specified
2
PD]
2
CD]
2
distribution between a lower
2
cumulative probability distribution for specified values.
F
distribution
F
cumulative probability distribution for specified values.
Mean: 6
t
CD]
f (x) =
1
p =
df
Γ
2
CD]
n + d
Γ
2
f (x) =
n
d
Γ
Γ
2
2
Q G
K
Q
Q
×
S
Q
G
G
K
K
[
Q ² [
I [
&
S
²S
Q
[
: probability of success (0 s
p
n
: number of trials
Chapter 7: Statistics Application 152
∞
df
df
–1
–
2
1
1
2
x
e
2
df
Γ
2
df
b
df
x
1
2
–1
–
2
2
x
e
dx
2
a
2
∞
n
n + d
n
–
–1
.
2
2
n
n
x
2
x
1 +
d
d
Q G
E
²
Q
Q [
²
×
G[
[
G
D
∞
[
Q
s 1)
p
Y
P
t
[
²
H
I [
[
x
(
= 0, 1, 2, ...)
: mean (0 < )
x
2
[
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