Difference between revisions of "Sigma"

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Most have heard of the "bell curve" in mathematics.  This is the shape that describes the probability that a given percentage of measurements will fall within a certain region under a standard bell curve.  This shape is found in nature - so its one that mathematicians use often.
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Most have heard of the "bell curve" in mathematics.  This is the shape that describes the probability that a given percentage of measurements will fall within a certain region under a standard bell curve.  This shape is found in nature - so its one that mathematicians use often to predict the chance that something will occur in nature.
  
 
This shape of the standard bell curve is called "Normal Distribution" or "Gausian Distribution."
 
This shape of the standard bell curve is called "Normal Distribution" or "Gausian Distribution."

Revision as of 00:34, 4 October 2011

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SIGMA and ERRORS

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Contents


Most have heard of the "bell curve" in mathematics. This is the shape that describes the probability that a given percentage of measurements will fall within a certain region under a standard bell curve. This shape is found in nature - so its one that mathematicians use often to predict the chance that something will occur in nature.

This shape of the standard bell curve is called "Normal Distribution" or "Gausian Distribution."

Bellcurve.jpg


HOW SIGMA PERTAINS to the BELL CURVE

A statistical measurement called "standard deviation" is also referred to as the region between the two sigma lines on the horizontal axis of a bell curve. The region between the two lines under the bell are is the region called "1 sigma". The lower case Greek letter sigma is used like this:

Sigma.jpg

The sigma symbol is combined with numbers like this to help us know how many sigma regions we are referring to: This is a probability of how much the measurements vary from the center value of the bell by a distance defined as sigma on either side of that center. (See + and - sigma in the graph above.)

Plus 1 sigma.jpg

"1 SIGMA" = 68% Chance (Fromto1sigma.jpg)

If someone says that an error is 1 sigma, then that person is referring to the greatest possible error in between the lines marked with - 1 sigma to + 1 sigma in the bell curve (see the curve above). Add the percentages of the two regions under the bell to get about 68%. There is a 68% chance that the error will not exceed the value stated.

"2 SIGMA" = 95% Chance (Fromto2sigma.jpg)

If someone says that an error is 2 sigma, then that person is referring to the greatest possible error in between the lines marked with -2 sigma to +2 sigma in the bell curve (see the curve above). Add the percentages of the four regions under the bell between the - and + sigma lines to get about 95%. There is a 95% chance that the error will not exceed the value stated.

"3 SIGMA" = 99.6% Chance (Fromto3sigma.jpg)

If someone says that an error is 3 sigma, then that person is referring to the greatest possible error in between the lines marked with -3 sigma to +3 sigma in the bell curve (see the curve above). Add the percentages of the six regions under the bell to get over 99%. There is a 99.6% chance that the error will not exceed the value stated.

How "2 SIGMA" applies to VTube-LASER SEF2 Values

The 2 Sigma value is used quite a bit for measuring. For example, when VTube-LASER reports Cylinder Fit errors, it always shows the values as "SEF2" or "standard error fit X 2" - which is the same as 2 sigma or (2 times the sigma) value calculated. This lets you know there is a 95% chance that the error or deviation reported in the Cylinder Fit window will not exceed that value.

Vtube-laser 1 58 cylinderfit highlight.jpg