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Re: Re: Normal Probability plot

  • To: mathgroup at smc.vnet.net
  • Subject: [mg91779] Re: [mg91700] Re: Normal Probability plot
  • From: "Youness Eaidgah" <y.eaidgah at gmail.com>
  • Date: Sun, 7 Sep 2008 22:53:25 -0400 (EDT)
  • References: <200809060605.CAA19615@smc.vnet.net>

Thank u all for ur reply (Bill and peter). Your suggested solutions
work fine and they helped me out.
Also, I am interetstd to plot my data on a standard normal probability
paper. is it possible to make a normal probability paper with Mathematica? On
a normal probability paper, one axe blongs to population(set of data) and
another one, vertical axe mostly, belongs to cumulative distribution. last
axe is sacled specially.
Best regards,

On Sat, Sep 6, 2008 at 8:05 AM, P_ter <petervansummeren at gmail.com> wrote:

> I mostly check the model (in this case the normal distribution) against the
> data with Quantiles:
>  myq = 100000;
> data = Sort@RandomReal[NormalDistribution[5, 1], { myq}];
> ListPlot[Transpose@{Quantile[NormalDistribution[0, 1], (Range@ myq - .5)/
> myq],data}, Frame -> True, Axes -> None]
> The ListPlot looks beautiful, but!
> First I make a list of the result of FindFit:
> varmed = FindFit[Transpose@{Quantile[NormalDistribution[0, 1],(Range@ myq
> - .5)/ myq], data},a x + b, {a, b}, x]
> myy = Quantile[(data - varmed[[2, 2]])/varmed[[1, 2]], (Range@ myq - 0.5)/
> myq];
> myx = Quantile[NormalDistribution[0, 1], (Range@ myq - .5)/ myq];
> mp = Transpose@{myx, myy - myx};
> ListPlot[mp]
> One can observe how the quantiles of the data (no sample correction) fit
> the quantiles of the model.
> In the above example they both come from the normal distribution.
> with friendly greetings,
> P_ter
>
>



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