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 2022-09-19, 23:50 #1 sticky   Nov 2020 22 Posts Gaussian Distribution Hello Folks, I was going through some articles and found a statement that is not very clear to me. Can you please help me understand it ( any available literature would help too). The statement goes as below: "The CDF of a Gaussian distribution can be expressed as a linear if the graph is drawn in a sigma-scale for the y-axis" I having a hard-time understanding the statement and process of have to convert the CDF to linear scale. Regards
 2022-09-22, 18:23 #2 MattcAnderson     "Matthew Anderson" Dec 2010 Oregon, USA 4A716 Posts Hi Sticky and others, A Gaussian distribution, or bell curve can be characterized by two variables. First is its mean, or center value. Second is its standard distribution, or wideness. See wikipedia https://en.wikipedia.org/wiki/Normal_distribution Have a nice day. Matt
 2022-09-22, 21:28 #3 MattcAnderson     "Matthew Anderson" Dec 2010 Oregon, USA 3×397 Posts Also, I did a Google search for "CDF normal distribution" I got this link https://www.probabilitycourse.com/ch...2_3_normal.php Have a nice day. Matt
 2022-09-25, 15:32 #4 sticky   Nov 2020 22 Posts Hello MattcAnderson, Thanks for the reply,I understand what CDF and Gaussian distribution are. What I dont understand is " graph is drawn in a sigma-scale for the y-axis"". CDF drawn with sigma-scale for y -axis? Regards Sundeep
2022-09-25, 17:54   #5
Batalov

"Serge"
Mar 2008
Phi(4,2^7658614+1)/2

19·232 Posts

Quote:
 Originally Posted by sticky What I dont understand is " graph is drawn in a sigma-scale for the y-axis"".
It is easy to understand by analogy. Suppose you have some variable that has an exponential behavior (for example any biological effect that is measured by luminescence, e.g. gene expression). To make it look linear, you change the plot to have y-axis transformed by the function inverse to exponent. What function is this? It is log().

Same here. CDF is known to have a wave-like, monotone function, usually denoted ๐ท() that describes it (when underlying distribution is normal). How do you transform y-axis? You apply the inverse function ๐ท-1(). It doesn't have an analytic expression but that doesn't matter - you can use a function that is indistinguishable from precise function, within pixels on your screen - you will not know the difference. So that's what programs like SigmaPlot do. It is rather simple.

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