Quote:
Originally Posted by chris
 Is the question asking which statistics (v_1, v_r and v_min) fit the assumptions underlying application of the Hoeffding inequality for estimating the bias of an individual coin (i.e. mu = out of sample probability of a head)?

Correct
Quote:
 Is it fair to say that Hoeffding can be applied to any of these statistics as long as mu reflects the out of sample distribution of that statistic?

Hoeffding involves both insample and outofsample frequencies, so just
(out of sample) may not suffice.
Quote:
 What is the appropriate value of N when applying Hoeffding to the average of 100,000 repetitions of the average number of heads realised by 10 coin flips? Is it 100,000 or 1,000,000? Seems to me that the overall process is equivalent to averaging the number of heads over 1,000,000 coin flips?

If the basic event here involves 10 coin tosses (say the event being that the number of heads out of 10 tosses is 10), and that experiment is repeated 100,000 times, then
of the Hoeffding inequality is 100,000.