JimP,
A couple of questions. Your first graph; is that a Line graph (with the x axis values sorted) or an XY graph? If it is a Line graph, how did you get the Jupiter distance to be even increments of 0.03? And if it is a Line graph, and your distance data is not absolutely equal increments, you have to really doubt the values of your linear regression. Redo it as a true XY and see what kind of regression you get.
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Then I added the monthly sunspot numbers data from 1749 to the present to the distances raw data spreadsheet. I have 3110 records. Everything was then sorted by Jupiter’s distance from the Sun. Next I calculated the average number of sunspots per 4 month period—steps of .028281 in distance. This is what I came up with. What do you think?
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And why did you group the numbers? Why not just graph the 3110 records?
As far as your last graph (post #15), again, why did you bunch them in 10 sunspot increments? Why not just graph all the individual values, instead of grouping them?
But lets say all of this is true and there are statistical correlations? You have to remember that correlation doesn't prove cause and effect, you have to find a mechanism that explains it. I could just as easily say that the number of sunspots changes the distance between the sun and Jupiter.