Representing a point in an n-dimensional space in a 2D geometrical shape

Alan P Smith

Is it possible for me to use a Voronoi diagram - or some other algorithm - to represent a point in an multidimensional space (between 5 and 10 dimensions) in a 2D geometrical shape? (And more interestingly, in a geometrical shape that is a) fairly small, and b) looks aesthetic.

I have a number of measurements in standard deviation units on different normal distributions. Say I have 8 standard deviation measurements on 8 different variables. This gives me the following numbers (one for each normal distribution):

1: -0.3
2: 1.2
3: 0.7
4: 2.1
5: 0.2
6: -1.3
7: -0.2
8: 1.9

Can I represent these 8 SD measures as a 2D geometrical shape (to encode them) in such a way that the 2D shapes distinguish between e.g. 10ths of a standard deviation unit (to a level of resolution as in this list)? What are my options here?

Thanks... Alan