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Bivariate density plots are computed
exactly the same way as are contour plots (equal probability contouring).
This algorithm generates, in general, graphs which are most accurately
interpreted by our brains, in terms of relatively frequencies of subpopulations.
All contouring algorithms have advantages and disadvantages, but probability
contours have the fewest disadvantages.
There are two types of density plots: grey-scale
and pseudo-color. They are identical, except the color scheme is
different. Grey-scale may be more acceptable for publication; pseudo-color
may be more acceptable for slide presentations.
There are two options that apply to density plots:
smoothing and high resolution. The graphs below (shown for pseudo-color
plots) show the effect of these options. Note that with smoothing
off, every event gets a dot; thus, this plot is much better than
dot plots, since it allows the simultaneously information of rare
events (dots) and high-frequency areas (dots of a different color).
You might choose low resolution to make data easier
to see in presentations: the small dots can be hard to see
on slides.
You may view a comparison
of all the bivariate displays for this
same data.
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