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3

It is a bug in the caching feature. Some distributions don't have p-value corrections since those based on the empirical CDF must be derived individually. The result is correct but the p-value is inflated due to lack of correction. When the test or any underlying one is ran again it returns the cached result with no message.


5

summing random numbers between -0.5 and 0.5. the number of numbers to be summed is very large, like a 1000000 for example. The sum of $n$ identical Uniform random variables is known as a generalised Irwin-Hall distribution, implemented in Mathematica as the UniformSumDistribution [ see kguler's answer]. The latter takes an $n$-part piecewise ...


8

The built-in function UniformSumDistribution may be useful: usd[n_] := UniformSumDistribution[n, {-.5, .5}]; Plot[Evaluate[PDF[usd@#, x] & /@ Range[20]], {x, -2, 2}, PlotStyle -> (ColorData[{"Rainbow", {1, 20}}] /@ Range[20]), Exclusions -> None, PlotRange -> All, ImageSize -> 500, PlotLegends -> ("usd (" <> ToString[#] ...


2

You are attempting to model a non-linear process with a linear model. Use a non-linear model. For example: NonlinearModelFit[data, {b Log[a x] + c, c > 0}, {a, b, c}, x] That should give a more reasonable answer. However, if I understand the game correctly there are a finite number of single-use clicks available to it. It would be interesting to ...



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