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Representing a point in an ndimensional space in a 2D geometrical shape 
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Dec1609, 03:25 PM

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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 


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