Difference Between Population and Sample

Understanding the difference between population and sample is easy if you remember one fundamental law of statistics: A sample is always a smaller group (subset) within the population.

In market research and statistics, every study is done with a basic inquiry at hand. This inquiry is conducted by observing or experimenting with a sample of the population, in order to derive insights that explain a phenomenon within the whole population.

What Is Population?

Population in research is defined as a complete set of elements that possess a common parameter between them.

Needless to say, we are all aware of what the word ‘population’ means in our everyday life. Oftentimes it is used to describe the human population or the total number of people living in a geographic area of our country or state.

Population in research doesn’t necessarily have to be human. It can be any collection of data that possess a common parameter.

Example. The total number of ‘Pet’ Stores on Sunset Boulevard in Los Angeles, California.

What is a Sample?

A sample is defined as the smaller part of the whole i.e a subset of the entire population. It is representative of the population in a study. When conducting surveys, the sample is the members of the population who are invited to participate in the survey. Hence, simply said, a Sample is a subgroup or subset within the population, that can be studied in order to investigate the characteristics or behavior of the entire population data.

Samples of data are created using various research methods like probability sampling and non-probability sampling. Sampling methods vary according to research types, based on the type of inquiry and the quality of information required.

Example: A cat food company would like to know all the pet stores where it can sell its canned fish. The company has population data on the total number of pet stores on Sunset Boulevard.

This pet food manufacturer can now create an online research sample by only selecting the pet stores that sell cat food. The data can be studied for various characteristics and the results can be displayed in statistics and reports analyzed for business insights. Using data from the sample the company can uncover ways to grow its business into the total population of pet stores.

Population Vs Sample

Usually, a Sample of the population is used in research, as it is easier and cost-effective to process a smaller subset of the population rather than the entire group.

In this table, we can take a closer look at the difference between sample and population:



The measurable characteristic of the population like the mean or standard deviation is known as the parameter. The measurable characteristic of the sample is called a statistic.
Population data is a whole and complete set. The sample is a subset of the population that is derived using sampling.
A survey done of an entire population is accurate and more precise with no margin of error except human inaccuracy in responses. However, this is not always possible. A survey done using a sample of the population bears accurate results, only after further factoring the margin of error and confidence interval.
The parameter of the population is a numerical or measurable element that defines the system of the set. The statistic is the descriptive component of the sample found by using sample mean or sample proportion.  

Top seven reasons to use a sample:

  • It is practical

In most cases, a population can be too large for a researcher to collect accurate data considering the constraint of size. A sample offers a representation of the entire population, that is sampled accordingly. Samples allow researchers to collect data that can be analyzed to offer insights into the whole population.

  • It offers urgent data

When it comes to research, the amount of time available can be a defining factor for a study. A sample offers a smaller set of the population for review, that delivers data that can be used to represent the entire population. Conducting a survey on a smaller sample, as opposed to the entire population can save precious time for researchers.

  • It is cost effective

The cost of conducting research is often a parameter for the study. Researchers must do the best with the resources they have at hand, in order to carry out a study and gain accurate insights. Conducting a study on a representative sample of a population is cost-effective as it requires fewer resources – like computers, researchers, interviewers, servers, and data collection centers.

  • It possesses accuracy of the representation

Depending on the method of sampling, research conducted on a sample can be accurate with lesser non-response bias, than if conducted by census. A sample that is selected using the non-probability method is an accurate representation of the population, and data collected can be used to gather insight about the whole population.

  • It offers inferential statistics

Inferential statistics is a process by which representative data is used to infer insights about the entire population. Inferential statistics are based on the concept of using data collected from a sample to deduce data that represents the entire population. Inferential statistics can only be collected using data samples.

  • At times, a sample is more accurate than a census

A census of an entire population does not always offer accurate data due to errors such as inconsistency in responses, or non-response bias. A carefully obtained sample, however, does away with this bias and offers more accurate data – that adequately represents the population.

  • It is manageable

Sometimes, collecting an entire population of data is near impossible as some populations are too difficult to come by. In this case, a sample can be used to represent the study as it is feasible and accessible.

Conclusion: In spite of the fact that Population and Sample are two different terms, they both are related to each other, i.e. samples are drawn from the population. The primary objective of the sample is to make statistical inferences about the population. Without population, samples can’t exist. The better the quality of the sample, the higher is the level of accuracy of generalization. 

Right sampling is very necessary to conduct insightful market research. Explore samples with QuestionPro Audience.