Before discussing the concept of sampling in statistics, first, we will first define the population and sample

Definition of Population, Sample and Sampling in Statistics

In statistics, the population is referred to as a whole, that is, it is an entire collection of objects, living or nonliving, that are being studied. It can be a group of people, items, events, organisations, etc.

Population or Universe

For example, the group of all students of a university is a population.  You use populations to draw conclusions.

Population or Universe

It is obvious that for any statistical investigation complete enumeration of the population is rather impracticable most of the time since population sets tend to be quite large.

Population or Universe

For example, if we want to know the average per capita (monthly) income in a country, we must first identify all of the earning individuals in the country, which is rather a very difficult task.

Population or Universe

In this case, we take the help of Sampling Unless the information is required for each and every unit in the domain of study, the sampling technique is generally used to obtain the information.

A sample is a finite subset of individuals from a larger population. That is, a sample is only a part or subset of a population.

Sample

The sample size is defined as the number of individuals (elements) in a sample.

Sample Size

The process of selecting a sample from a population is known as sampling.

Sampling in Statistics

In the sampling method, instead of studying every unit of the population, only a part of the population (sample) is studied and drawing conclusions for the entire population on that basis.

Sampling in Statistics

For the purpose of obtaining characteristics of a population,  we observe the individuals in the sample only instead of enumerating the entire population.  Then these sample characteristics are used to approximate or estimate the population.

Sampling in Statistics

For example,  after checking a sample of a particular item, we decide whether to purchase or reject it.

Sampling in Statistics

Despite the fact that much of the development in sampling theory has occurred in recent years, the concept of sampling is quite old. Sampling is frequently used in our everyday lives.

Examples of Sampling

(1) A doctor examines a few drops of blood and draws conclusions about the blood constitution of the whole body.

Examples of Sampling

(2) A housewife normally tests the food to find if they contain the proper quantity of salt or sugar.

Examples of Sampling

(3) A housewife examines only two or three grains of boiling rice to know, whether the rice is cooked or not.

Examples of Sampling