Re: Normal Probability plot

*To*: mathgroup at smc.vnet.net*Subject*: [mg91641] Re: Normal Probability plot*From*: Bill Rowe <readnews at sbcglobal.net>*Date*: Sat, 30 Aug 2008 01:52:38 -0400 (EDT)

On 8/29/08 at 4:11 AM, y.eaidgah at gmail.com (Youness Eaidgah) wrote: >I have a set of data and I want to plot them on a normal probability >plot, to verify their normality. How can I make a normal probability >plot by Mathematica? In addiction, is it possible to find the best >straight line which fit the data? All of this is possible. How much effort it would require depends on precisely what you want. I could interpret "normal probability plot" as plotting the empirical distribution function versus quantiles of the normal distribution. A plot that might work for you that is relatively simple would be: data = Sort@RandomReal[NormalDistribution[5, 1], {20}]; ListPlot[Transpose@{Quantile[ NormalDistribution[0, 1], (Range@20 - .5)/20], data}, Frame -> True, Axes -> None] And FindFit can be used to find the parameters of the best fit line by doing: In[12]:= FindFit[ Transpose@{Quantile[NormalDistribution[0, 1], (Range@20 - .5)/20], data}, a x + b, {a, b}, x] Out[12]= {a->0.877822,b->4.90027} However, if your data is from a normal distribution it is more efficient to do: In[13]:= {Mean[data], StandardDeviation[data]} Out[13]= {4.90027,0.885315}