be biased. The point is that after the relevant strata in a population are identified, the actual choosing of sample households or respondents should be a matter of pure chance. This can be ensured in various ways. Different techniques are used to achieve this, the common ones being drawing of lots (or lottery), rolling of dice, the use of random number tables specially produced for this purpose, and more recently, random numbers generated by calculators or computers.
To understand how a survey sample is actually selected, let us take a concrete example. Suppose we wish to examine the hypothesis that living in smaller and more intimate communities produces greater intercommunity harmony than living in larger, more impersonal communities. For the sake of simplicity, let us suppose we are interested only in the rural sector of a single state in India. The simplest possible sample selection process would begin with a list of all villages in the state along with their population (Such a list could be obtained from the census data).
Then we would decide on the criteria for defining ‘small’ and ‘large’ villages. From the original list of villages we now eliminate all the ‘medium’ villages, i.e. those that are neither small nor big. Now we have a revised list stratified by size of village.
Given our research question, we want to give equal weightage to each of the strata, i.e. small and big villages, so we decide to select villages from each. To do this, we number the list of small and big villages, and randomly select numbers from each list by drawing lots. We now have our sample, consisting of big and small villages from the state, and we can proceed to study those villages to see if our initial hypothesis was true or false.
Of course, this is an extremely simple design; actual research studies usually involve more complicated designs with the sample selection process being divided into many stages and incorporating many strata. But the basic principles remain the same — a small sample is carefully selected such that it