Population and sample

Every time we hear the term “population,” the first thing that comes to mind is a large group of people. Similarly, in statistics the population denotes a large group that have at least one common characteristic. The term is often contrasted with the sample , which is no more than a part of the population that is selected to represent the whole group.

MeaningThe population refers to the collection of all the elements that have common characteristics, which comprises the universe.Sample means a subset of the members of the population chosen to participate in the study.
It includesEach and every one of the units in the group.Only a handful of population units.
Data collectionComplete enumeration or censusSample or sampling survey
Focus onIdentify the characteristics.Make inferences about the population.

Definition of population

In simple terms, population means the set of all the elements under study that have one or more common characteristics , for example, all the people living in India constitute the population. The population is not just limited to people, but can also include animals, events, objects, buildings, etc. It can be of any size, and the number of elements or members of a population is known as the population size, that is, if there are 100 million people in India, then the population size (N) is 100 million . The different types of population are presented below:

  • Finite Population: When the number of elements in the population is fixed and therefore it is possible to list it in its entirety, the population is said to be finite.
  • Infinite population: When the number of units in a population is uncountable and therefore it is impossible to observe all the elements of the universe, the population is considered infinite.
  • Existing population : The population that is made up of objects that actually exist is called the existing population.
  • Hypothetical population : The hypothetical or imaginary population is the population that exists hypothetically.


  • The population of all workers working in the sugar factory.
  • The population of motorcycles produced by a particular company.
  • The mosquito population in a city.
  • The taxpayer population in India.

Sample definition

By the term sample, we mean a part of the population randomly chosen to participate in the study . The sample thus selected must be such that it represents the population in all its characteristics, and must be free of bias, in order to produce a miniature cross-section, since the observations of the sample are used to make generalizations about the population.

In other words, the respondents selected from the population constitute a ‘sample’ , and the process of selecting respondents is known as ‘sampling’. The units under study are called sampling units, and the number of units in a sample is called the sample size.

When performing statistical tests, samples are used primarily when the sample size is too large to include all members of the study population.

Key differences between population and sample

The difference between population and sample can be clearly established for the following reasons:

  • The collection of all the elements that have common characteristics that comprise the universe is known as the population. A subset of the members of the population chosen to participate in the study is called a sample.
  • The population consists of each and every one of the elements of the entire group. On the other hand, only a handful of items from the population are included in a sample.
  • The characteristic of the population based on all units is called the parameter, while the measure of the observation of the sample is called the statistic.
  • When information is collected from all population units, the process is known as a census or complete enumeration. Rather, the sample survey is conducted to collect information from the survey using the sampling method.
  • With the population, the objective is to identify the characteristics of the elements, while in the case of the sample; The emphasis is on generalizing about the characteristics of the population, where the sample comes from.

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