This part deals with tests on proportions. After the Gaussian distribution the binomial distribution is probably the next most famous distribution. Binomial samples are very common and more intuitive than a Gaussian distribution. Ill and healthy, success and failure, poor and rich are well known binomial outcomes. The binomial distribution is linked to the normal distribution via large sample approximation and the normal distribution is the square root of the -distribution. More importantly, the binomial distribution is a special case of the multinomial distribution. This distribution plays a crucial role in the analysis of contingency tables and the tests in Chapter 4 can also be described in a contingency table set-up. However, this topic in general is covered in Chapter 14. Here we deal with well known special cases. Often the question occurs, if a proportion is the same as a predefined value or if two (or more) proportions differ significantly from each other.