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I have DAta base that having three features average , standard deviation and variance of 10 image which in arrays looks like this
Average standard Deviation Variance
63 12192 110
63 12103 110
64 12258 110
73 13331 115
88 14740 121
69 12937 131
79 13824 117
63 12192 110
65 12207 110
I have to make patterns .. Of these values . Mathematically it seems to me difficult .
but i think i should apply nested loop . and make patterns .
and then test my input image statistic with the patterns that we can get using nested loop . .
Is there a simple way in maths to get patterns of the above values .
Please help me Thanks
Maths is Doctor that make our life easy ..
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Hi model;
I do not understand your question. What kind of patterns? Do you want to fit equations to the data? Like a regression analysis?
In mathematics, you don't understand things. You just get used to them.
If it ain't broke, fix it until it is.
Always satisfy the Prime Directive of getting the right answer above all else.
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Hi model;
I do not understand your question. What kind of patterns? Do you want to fit equations to the data? Like a regression analysis?
Hi ,
pattern making like tree diagram .. or in form of set pair.
Maths is Doctor that make our life easy ..
https://www.facebook.com/groups/Maths.GIS/
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Hi model;
I am not saying I can help but I am not understanding at all. Could you show what you mean?
In mathematics, you don't understand things. You just get used to them.
If it ain't broke, fix it until it is.
Always satisfy the Prime Directive of getting the right answer above all else.
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hi
If these are the results of 9 samples from a population, then we can estimate population statistics.
Or test 'Are these samples all from the same population?' (Not very reliably.)
But I'd like to know the sample sizes.
Beyond that I'm at a loss too.
Bob
Children are not defined by school ...........The Fonz
You cannot teach a man anything; you can only help him find it within himself..........Galileo Galilei
Sometimes I deliberately make mistakes, just to test you! …………….Bob
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