1.1 INTRODUCTION TO SAMPLING THEORY In this sub-unit, the need for taking a sample so as to make generalizations about the population from which the sample is drawn, and the advantages and disadvantages of sampling over census will be presented. The main purpose is to introduce some techniques of sampling-which are broadly classified into non-random sampling and random sampling. 1.1.1 BASIC CONCEPTS OF A SAMPLE SURVEY Population is the totality of all subjects (possessing certain common characteristics) that are being studied. It is the collection of all the units under investigation, which consists of a specified type of persons or objects over a given space and time. Population should be defined on the basis of the objective of the study by the investigator. An important step towards sample survey involves carefully defining the population from which the sample will be taken. If for example, a researcher is interested in knowing the average weight of the Ethiopian male, then the population is the weights of all Ethiopian men - not all Ethiopian men. In other words, the population is the actual numbers representing the weight of each Ethiopian male. Now suppose that this same researcher is also interested in the average height of the Ethiopian male. In this case, the researcher must consider two populations even though he or she will be taking measurements from the same men, the population of all weights of Ethiopian men and the population of all heights of Ethiopian men. Reasons for Sampling Some specific situations of sampling include: i. When time, money and other resources are limited. ii. When census survey is not possible. iii. When the scope of investigation is very wide and the population is not known. iv. If the population is too large (e.g. trees in a jungle) or hypothetical (like tossing a coin) we are left with no alternative but to resort to sampling. v. If testing is destructive (breaking strength of chalk, life of an electric tube or bulb) complete enumeration is impracticable.