Statistics – Population:

Don’t get confused when we hear the word population, we typically think of all the people living in a town, state, or country. In statistics, a population is an entire group about which some information is required to be ascertained. A statistical population need not consist only of people.

We can have population of heights, weights, BMIs, hemoglobin levels, events, outcomes. In selecting a population for study, the research question or purpose of the study will suggest a suitable definition of the population to be studied, in terms of location and restriction to a particular age group, sex or occupation. The population must be fully defined so that those to be included and excluded are clearly spelt out (inclusion and exclusion criteria).

Example:

If we say that our study populations are all lawyers in Delhi, we should state whether those lawyers are included who have retired, are working part-time, or non-practicing, or those who have left the city but still registered at Delhi.

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 singareni, or pilgrims travelling to Kumbh Mela at Allahabad. The type of information gathering over a whole population by government is called a census.

The limitation of studying population is it is difficult to observe all the individuals in any given group. So, statisticians also study sub populations and take samples of large population to accurately analyze the full spectrum of behaviors and characteristics of the population at large. So, let’s learn about samples.