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Timeline for Density plot of (x1,x2) points

Current License: CC BY-SA 3.0

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Aug 6, 2017 at 22:42 vote accept user1993416
Aug 6, 2017 at 21:18 answer added JimB timeline score: 4
Aug 6, 2017 at 20:02 comment added user1993416 @JimBaldwin Thank you very much for your help. I would ask you to add something else to your second comment. It seems it would be better to manipulate the data before the representation. Would you explain something else about the suggested slices or give an example? Thank you very much
Aug 6, 2017 at 19:56 comment added user1993416 @J.M. Thank you very much SmoothDensityHistogram[] function is what I was looking for.
Aug 6, 2017 at 18:47 comment added JimB The plot described in my earlier comment will look a lot like yours. As far as exploring whether there is a non-zero correlation you might want to try a plot of the square-roots (or some other fractional power close to zero) on both variables to get the majority of the points in the middle of the figure. Alternatively, you could take slices of points say between 15 and 20 for x1 and between 100 and 105 for x1 and compare the resulting histograms for x2. If they differ much in any observed way, then further investigation of the correlation structure is warranted.
Aug 6, 2017 at 18:40 comment added JimB It's not obvious to me that there is a non-zero correlation. Consider the plot of two independent samples (where by definition there is no correlation): x1 = RandomVariate[LogNormalDistribution[3.5, 1], 50000]; x2 = RandomVariate[LogNormalDistribution[3.5, 1], 50000]; ListPlot[Transpose[{x1, x2}], PlotRange -> {{0, 250}, {0, 250}}, AspectRatio -> 1, AxesStyle -> White, TicksStyle -> Black].
Aug 6, 2017 at 18:33 comment added J. M.'s missing motivation Have you seen SmoothDensityHistogram[]?
Aug 6, 2017 at 18:19 history asked user1993416 CC BY-SA 3.0