Population and Sample
Research workers in the early 19th century endeavored to survey entire populations. This feat was tedious, and the research work suffered accordingly. Current researchers work only with a small portion of the whole population (a sample) from which they draw inferences about the population from which the sample was drawn. This inferential leap or generalization from samples to population, a feature of inductive or empirical research, can be full of pitfalls. In clinical medicine, it is not sufficient merely to describe a patient without assessing the underlying condition by a detailed history and clinical examination.The signs and symptoms are then interpreted against the total background of the patient's history and clinical examination including mental state examination. Similarly, in inferential statistics, it is not enough to just describe the results in the sample. One has to critically appraise the real worth or representativeness of that particular sample. The following discussion endeavors to explain the inputs required for making a correct inference from a sample to the target population. Use of the word population in epidemiological research does not correspond always with its demographic meaning of an entire group of people living within certain geographic or political boundaries. A population for a research study may comprise groups of people defined in many different ways, for example, coal mine workers in Dhanbad, children exposed to German measles during intrauterine life, or pilgrims traveling to Kumbh Mela at Allahabad.