In this excellent overview of the history of probability and nonprobability sampling from the end of the nineteenth century to the present day, Professor Graham Kalton outlines the essence of past endeavors that helped to define philosophical approaches and stimulate the development of survey sampling methodologies. From the beginning, there was an understanding that a sample should, in some ways, resemble the population under study. In Kiær’s ideas of “representative sampling” and Neyman’s invention of probability-based approach, the prime concern of survey sampling has been to properly plan for representing characteristics of the finite population. Poststratification and other calibration methods were developed for the same important goal of better representation.