Introduction

Abstract

In this second part of the book we discuss statistical methods for the two-sampleand the K-sampleproblems. Whereas in the one-sample problem the objective is to compare the distribution of the sample observations with a hypothesised distribution, we are now concerned with comparing the distributions of two or more populations from which we have observations at our disposal. As both classes of problems are about comparing distributions, many of the methods developed for the former can be easily adapted to the latter. We indeed show that many names of tests come back (e.g., the Kolmogorov–Smirnov and the Anderson–Darling tests). It also further implies that many of the building blocks of Chapter 2 are useful again.