Population and Sample are the two fundamental terms of Inferential Statistics. Inferential Statistics uses probability to draw inferences on the characteristics of Populations using Sample Data. As the size of the population is large, it is often impractical or too expensive to collect data from entire population. Hence a small manageable representative portion of population known as sample is used for the study of Population behavior.

A population consists of all subjects that are being studied. A sample is a subset or a group of subjects selected from the population.

For example, if the study is to involve the spending behavior of employed woman in US, the population will consist of all working woman in US. Hence for the study of spending behavior of working woman, a sample may consist of 250 working woman picked 5 each from 50 cities.
In certain cases for some reason all the subjects in the population will be included in the sample. Such a sample of entire population is known as Census. The characteristics of a population like mean or variance are called parameters and their sample counterparts are known as statistics.