Since each document in the corpus is assumed to be generated independently, z i 's are independent random variables and we can bound the deviation of the observed value of Z from its expectation using Hoeffding's Inequality -for any t > 0, we have Recall that Z models the number of documents supporting the hypothesis "α is an -significant wordpair.").
the upper-bound δ (= exp(−2Kt 2 )), 0 < δ < 1 denotes the upper-bound on the probability that just due to random chance, more than (E(Z) + Kt) documents out of K will support the hypothesis "α is an -significant word-pair."