# Standard Normal Distribution

333 views

### Gurveer

Jul 27, 2009, 12:36:41 AM7/27/09
to
Hi

I read many threads on this group related to calculating the normal
distribution but I couldn't find what I needed exactly. Is there any
way in the HP 50g to calculate the value of standard normal
distribution(area under the curve) using(given) just the z-values? For
eg:- Using the tables, 0.4772 is the value of standard normal
distribution for a z-value of 2.0 regardless of what the mean,
standard deviation or the data values were although I know that z-
value is calculated using these parameters.

Thank you.

Regards,

Gurveer

### Virgil

Jul 27, 2009, 1:08:50 AM7/27/09
to
In article
Gurveer <gurve...@gmail.com> wrote:

Are you familiar with the UTPN command?

If you put 0, 1 and z on the stack, in that order, then the UPTN command
returns the upper tail probability.

This will give you 0.5 minus your value of 0.4772, when rounded to 4
decimal places).

The 0 and 1 are for the mean and standard deviation, which are 0 and 1,
respectively, for the z distribution.

You can create a program to get your value directly from the z-score.
For example:
\<< 0. 1. ROT UTPN NEG .5 + \>>
will take a positive value on the stack as the z-score and return the
probability of a score being between 0 and that z-score.

--
Virgil

### Chazzy Chazz

Jul 27, 2009, 1:39:53 AM7/27/09
to
On Jul 26, 11:08 pm, Virgil <virg...@nowhere.com> wrote:
> In article

Thanks a lot Virgil. That's exactly what I wanted. Yeah, I'm somewhat
familiar with the command UTPN and the concept you told makes sense.
That's all I need and that simple program just works awesome for me.
Thank you once again.

Regards,

Gurveer

### Nate Eldredge

Dec 2, 2021, 3:02:15 AM12/2/21
to
> > If you put 0, 1 and z on the stack, in that order, then the UPTN command
> > returns the upper tail probability.
> >
> > This will give you 0.5 minus your value of 0.4772, when rounded to 4
> > decimal places).
> >
> > The 0 and 1 are for the mean and standard deviation, which are 0 and 1,
> > respectively, for the z distribution.

For anyone else finding this old post via Google search, the second argument (1 here) is in general NOT the standard deviation, but rather the variance (square of the standard deviation). In this example the variance is also 1, of course.