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#1
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I'm confused about the process of determining whether a particular random sample "satisfies" Hoeffding's inequality.
In particular, when we run some experiments and determine the average proportion of green marbles, we generate some averages for several ![]() ![]() ![]() ![]() ![]() I suppose my question is: how does a particular ![]() ![]() |
#2
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![]() Quote:
![]() ![]() ![]() ![]() The formal statement would not involve an individual ![]()
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#3
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Thanks, professor! That clears it up.
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#4
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Is Hoeffding's Inequality true for every experiment and hypothesis ? Is it possible that P[Ein -Eout] for some hypothesis is not bounded by 2exp( -2e2N) ?
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#5
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If you fix any hypothesis then run the experiment, the probability will always be bounded by that term.
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#6
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I am sorry, but I still dont get it. Let us say one person is tossing a fair coin 10 times and got all heads. Here one coin refers to one hypothesis correct ?, so that is fixed. N is also fixed to 10. Does this mean that this experiment would satisfy hoefding's inequality ?
I am confused by the statement that hoeffding's inequlity is universally true for fixed hypothesis and experiment. |
#7
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Thinking on it more...does it mean that if the experiment involves multiple iterations of flipping the same coin 10 times then it will be bounded by hoeffding's inequality?
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#8
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If you are applying Hoeffding to the 10 flips, and you are considering multiple attempts at 10 flips, then we are in the "multiple bin" rather than single bin regime. You can apply the regular (single bin) Hoeffding to all the flips considered together (N would be multiple of 10 given your description).
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