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#1 |
Nov 2020
22 Posts |
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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 |
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#2 |
"Matthew Anderson"
Dec 2010
Oregon, USA
4A716 Posts |
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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 |
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#3 |
"Matthew Anderson"
Dec 2010
Oregon, USA
3×397 Posts |
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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 |
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#4 |
Nov 2020
22 Posts |
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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 |
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#5 | |
"Serge"
Mar 2008
Phi(4,2^7658614+1)/2
19·232 Posts |
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Same here. CDF is known to have a wave-like, monotone function, usually denoted ๐ท() that describes it (when underlying distribution is normal). How do you transform y-axis? You apply the inverse function ๐ท-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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