Therefore under [H.sub.0] we have that [I.sub.A] and [I.sub.B] follow a
Bernoulli distribution with probability of success [p.sub.A] = 1/2 and [p.sub.B] = 1/2 respectively.
(19) Here is the
Bernoulli distribution for 10 tosses, number of heads along the bottom, number of occurrences from 1024 possibilities on the side: (see figure and table next page)
The
Bernoulli distribution determined by p is the probability distribution of a random configuration c [member of] [S.sup.Z] if the values [c.sub.i], for i [member of] Z, are chosen randomly and independently, each with distribution p.
A question having 'm' multiple choices when awarded marks either 0 or 1, implies that the marks is a random variable 'X' which has a
Bernoulli distribution i.e.
[3] shows that if we have a finite support discrete distribution such as the
Bernoulli distribution, then we can have the elements of the probability vector updated according to
Raghavan and Upfal have given a protocol in which the expected delay (time to get serviced) of every message is O(log n) when messages are generated according to a
Bernoulli distribution with generation rate up to about 1/10.
The
Bernoulli distribution is the appropriate distribution to use when multiple admissions are not possible.