For many of the distributions to be discussed in this text, it appears that as parameters are allowed to increase the resulting distribution becomes more and more symmetrical and more and more bell-shaped. This is indeed the case for the hypergeometric distribution. In general, you can check by seeing what happens to the skewness \(\gamma_1\) and the kurtosis \(\gamma_2\) and to see if \(\gamma_1 \rightarrow 0\) and \(\gamma_2 \rightarrow 3\text{.}\) If so, that is the definition for what is meant when a distribution is bell-shaped. Eventually, we will see that the "Normal Distribution" is the eventual model of a distribution that is always bell-shaped.