Reviewed by Annapoorna | Updated on Sep 25, 2022


What is Meant by Sample?

A sample is a smaller, more manageable version of a larger collection. It is a subset containing greater population characteristics. Samples are used in statistical research to include all potential participants or findings when sample sizes are too large for the study. A sample should represent the entire population and not show any prejudice against a particular attribute.

In other words, a sample is a collection of objective findings taken from a population. Whereas, a population is the total number of persons, objects, things, observations, records, etc. of any given subject. Therefore, a sample is a component, part, or fraction of the entire group and functions as a subset of the population.

Importance of Samples

Samples are used in a variety of environments where investigations are carried out. Among those who use samples for their studies and measurements are scientists, advertisers, government departments, economists, and study organisations.

In financial analysis and audit of financial statements, sampling is adopted to identify any material misstatements in the financial statements and to detect frauds.

There are difficulties in using the whole population for study, which is why samples are used. Researchers may have trouble accessing whole communities. Due to the complexity of such studies, researchers can find it challenging to get the results they need in a timely fashion.

That's why samples are used by people doing studies. Using a smaller number of people representing the whole population will still yield reliable outcomes while saving time and money. Researchers' samples should be closely analogous to the population. All study participants will have the same traits and qualities.

For example, the sample will be a small percentage of the male population who match this definition if the research is about male college freshers. Similarly, if a research group performs an analysis of single women's sleep habits over 50 years, the survey will include only people within this demographic.

The selection needs to be random to obtain an impartial sample so that everyone in the population has a fair and likely chance of being added to the sample community. It is similar to a lottery draw and is the basis for easy sampling at random.

Types of Sampling Explained

There are mainly two types of sampling as follows:

1. Simple Random Sampling is suitable if each individual within the population is the same. If the researchers do not care whether their sample subjects are male or female, or in any type a mixture of both sexes, the simple random sampling can be a good technique of selection.

2. Stratified Random Sampling refers to a method of sampling, also called proportional random sampling or quota random sampling. It divides the whole population into smaller categories known as strata. People share similar characteristics within the strata.

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