Fourth Principle of SPC – the shape is like a bell

Fourth Principle of SPC is logical extension of the third principle which is covered in my last post.  In which it was said that most measurements will be clustered around the middle. In Fact it was proved by statisticians that we can make failry accurate predictions of the percentage measurements in the various sections of the frequency distribution curve.

Fourth Principle of SPC - the shape is like a bell 1
Frequency curve with normal distribution
You can see this graph Most measurements fall clso to the middle. This is applicable in general. You will find about 68.2% (34.1%+34.1%)of the measurements will be in the two middle sections of this graph.
28%(14%+14%) of the measurements will fall within the next two sections after the middle sections.
About 4.2%(2.1%+2.1%) will fall in the two outside sections.
A very minute percentage of the measurements will fall outside these sections.  This seems to be a bit odd, bu this is a proven fact. However, absense of external conditions is mandatory.
This Curve shown above will be called as a normal distribution. In fact many statsistical theories are centered around the theme of Normal distibution.
The above example will lead to our fifth principle of Statistical Process Control (SPC)- It is possible ot determine the shape of the distribution curve for parts/output produced by any process.
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Originally posted 2012-03-03 02:14:00.

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