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My apologies if this comes out as stupid.

Problem (Domain : stock exchanges): I have been given the sum of orders placed per instrument(security or company) for about 25000+ instruments. So my dataset looks something like this:

[Instrument] [Order count]   [Average Order Size(AOS)]  [Orders above 10*AOS]     AAA            20                 10000.0                 ?    BBB            5000               24334.5                 ?    ................... 

I know the average order size placed for an instrument as shown above. I want to calculate an estimate for the number of orders placed which had a order size above 10*[average order size] per instrument. I don't have an idea about the distribution. Assuming it's a normal distribution, I don't have an idea about the standard deviation. Is there any way to get a practical answer (I don't care if it is a value in a range.) for my problem? I hope this question is relevant here. Thanks.

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    :(. Someone help!2011-02-14
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    There's simply not enough data out there to make an inference. Do you have any past data that you can harvest to get more insight on the distribution?2011-02-14
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    What about [Markov's inequality?](http://en.wikipedia.org/wiki/Markov's_inequality) You know that order sizes are always positive, so that should do it.2011-02-14

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