32
Math Functions
:expReg ae^(b
x
)
Fits the model equation y=a e^(bx) to the data
using least squares fit on linearised data for at
least two data points. It displays values for
a
and
b
; it also displays values for
r
2
and
r
.
% u "
displays the
DISTR
menu, which has the following distribution
functions:
1:Normalpdf
Computes the probability density function (
) for
the normal distribution at a specified
x
value. The
defaults are mean
mu
=0 and standard deviation
sigma
=1. The probability density function (pdf) is:
2:Normalcdf
Computes the normal distribution probability
between
LOWERbnd
and
UPPERbnd
for the
specified mean
mu
and standard deviation
sigma
.
The defaults are
mu
=0;
sigma
=1; with
LOWERbnd
=
M
1
E
99 and
UPPERbnd
= 1
E
99.
Note:
M
1
E
99 to 1
E
99 represents
M
infinity to infinity.
3:invNormal
Computes the inverse cumulative normal
distribution function for a given area under the
normal distribution curve specified by mean
mu
and standard deviation
sigma
. It calculates the
x
value associated with an area to the left of the
x
value. 0
{
area
{
1 must be true. The defaults are
area
=1,
mu
=0 and
sigma
=1.
4:Binomialpdf
Computes a probability at
x
for the discrete
binomial distribution with the specified
numtrials
and probability of success (
p
) on each trial.
x
is a
non-negative integer and can be entered with
options of SINGLE entry, LIST of entries or ALL (list
of probabilities from 0 to
numtrials
is returned). 0
{
p
{
1 must be true. The probability density
function (
) is:
5:Binomialcdf
Computes a cumulative probability at
x
for the
discrete binomial distribution with the specified
numtrials
and probability of success (
p
) on each
trial.
x
can be non-negative integer and can be
entered with options of SINGLE, LIST or ALL (a list
of cumulative probabilities is returned.) 0
{
p
{
1
must be true.
6:Poissonpdf
Computes a probability at
x
for the discrete
Poisson distribution with the specified mean
mu
