Inferential Statistics and Distributions 13-31
8313INFE.DOC TI-83 international English Bob Fedorisko Revised: 02/19/01 12:47 PM Printed: 02/19/01 1:38 PM
Page 31 of 36
tcdf(
computes the Student-
t
distribution probability
between
lowerbound
and
upperbound
for the specified
df
(degrees of freedom), which must be > 0.
tcdf(
lowerbound
,
upperbound
,
df
)
c
2
pdf(
computes the probability density function (pdf) for
the
c
2
(chi-square) distribution at a specified
x
value.
df
(degrees of freedom) must be an integer > 0. To plot the
c
2
distribution, paste
c
2
pdf(
to the
Y=
editor. The probability
density function (pdf) is:
f x
df
x
e
x
df
df
x
( )
(
)
(1 / 2)
=
≥
−
−
1
2
0
2
2
1
2
Γ
/
,
/
/
/
c
2
pdf(
x
,
df
)
Note: For this example,
Xmin = 0
Xmax = 30
Ymin =
L
.02
Ymax = .132
c
2
cdf(
computes the
c
2
(chi-square) distribution probability
between
lowerbound
and
upperbound
for the specified
df
(degrees of freedom), which must be an integer > 0.
c
2
cdf(
lowerbound
,
upperbound
,
df
)
tcdf(
c
2
pdf(
c
2
cdf(