NavList:

Having informed myself (when you're looking for a helping hand its always waiting there, right at the end of your arm) that a "Gaussian distribution" is quite simply a standard distribution, and that positive kurtosis appears to be simply the opposite, and that leptokurtotic boils down to excessive positive kurtosis (however that is defined) I may now make so bold as to comment on the relevance of this jargon to the slope. 

I guess we all know now what slope means; a methodology for the evaluation of a series of sights taken over a short period, but for the sake of anyone who may have tuned in recently, first a short diversion as to why the observation period must be short.

Its because drawing the calculated (=real) slope as a straight line is an approximation of a short portion of an arc (same as position lines).  The extent of curve of that arc varies with the position of the body in the sky, but as a practical 'rule of thumb' the maximum period of time is assumed to be 5 minutes (for star/planet sights at dawn or dusk the available window of opportunity is, of course, another time-limiting factor).

Therefore the number of timed sights that can be recorded is limited by those 5 available minutes (mind you, if other factors allow you can go on taking sights then choose the 5-minute period you prefer - perhaps avoiding altogether any apparent outliers).

How many timed sights can you record in 5 minutes?  If I have to record them myself its about 4 to 6, thus roughly one per minute - others may be faster.  If I have a scribe then more, and I have posted here an example of 9 sights.

The relevance of this to whether the distribution is standard or not lies in the disproportionate effect 1 or 2 outliers can have.  If both outliers lie to the same side of the slope, as they do in my 9-sight example, then they could lead to significant error if averaged blindly, and to adoption of a significantly erroneous slope if this is derived via linear regression.

In other words, because the population is so small a significantly non-Gaussian distribution or a leptokurtotic event, if this is the jargon you prefer, is always going to be likely.