My question is related to this: Hash-Table in Practice
In [1] page 7, it is said that if we throw $n$ balls into $k$ bins, then each bin contains at most $\frac{n}{k}+O(\sqrt[2]{(\frac{n}{k})\log k}+\log k)$ elements with a high probability.
Question 1: Why is $O()$ used in the above estimation?
Question 2: Does it mean the probability that a bin contains more than the above value is negligible?