population vs sample
May 31, 2024
Author : Jess Healy

In statistical analysis of population vs sample, the quality of the result hinges on the integrity of the data. The data employed must be appropriate and representative of all pertinent categories. Therefore, while gathering more data improves the impartiality of outcomes, it is imperative to ensure that the data collected is relevant to the particular issue being addressed. However, one of the effective ways to ascertain this relevance is learning and understanding the distinction between population and sample.

This tutorial will equip you with a comprehensive learning and understanding of sample vs population in dissertation. Furthermore, the population donates the entirety of individuals under consideration for conclusion. Conversely, a sample refers to the subset of individuals from which data will be gathered in one place. Moving forward, in this web blog, we will not only study the key differences between population and sample but also look into the effective ways of collecting data in population and sample. So, read this write-up till the end to get precise knowledge.

What Is Population?

Population encompasses the complete set of individuals or items that pique a student’s interest in the study. However, it might encompass people, plants, animals, objects or any other grouping. For example, if a student aims to investigate the dietary patterns of all adults within a particular country, the population would consist of all adults residing in that country. Let’s continue with population vs sample and its effective ways to collect data.

What are the Effective Ways of Collecting Data From a Population?

Gathering data from a whole population can be difficult, especially if the population is large or geographically dispersed. However, there are several approaches students can use to collect data from a population:

1. Administrative Data

Using existing administrative databases or records maintained by government agencies, institutions or organisations. These records often contain valuable information about individuals or items within a population. Therefore, it includes census data, healthcare records, text records or educational records.

2. Surveys

In between sample vs population in dissertation, surveys involve administering interviews or questionnaires to a representative of a population sample. Likewise, while surveys are often used for sampling, they can also be employed to gather appropriate data from the entire population if feasible. However, this method allows students to gather information directly from individuals. Similarly, it provides insights into their opinions, behaviours and characteristics.

3. Direct Observation

Observing and recording information about individuals or items within the population firsthand is the common method in anthropology, sociology, and ecology, where students observe natural behaviours in their environment.

4. Remote Sensing

In the section on population vs sample, use remote sensing technologies such as drones, sensors, or satellites to gather data about environmental features of phenomena within a population. Therefore, remote sensing is specifically useful for studying huge geographical areas or inaccessible locations.

5. Social Media and Web Data

Analysing data generated from social media platforms, online communities or websites to comprehend the behaviours, interactions and preferences of individuals within the population can provide useful insights into digital populations and online communities.

6. Physical Measurements

The physical measurement method involves taking physical samples or measurements from individuals or items within the population. Moreover, it is commonly used in biology, engineering, and medicine to collect purpose physiological characteristics or properties data.

7. Ethnographic Research

While studying sample vs. population in dissertation, you will learn about the vital section of the population that is ethnographic research. Hence, ethnographic research involves immersing oneself in the culture or community of interest to understand the population’s beliefs, social dynamics, and practices deeply. It often involves much longer participant observation and engagement.

What Is a Sample?

A sample is a subset of items, observations or items selected from a wide group or population to represent the characteristics of that huge group. In other words, it is a smaller, manageable portion of a population study to make inferences about the entire population.

Important is Population And Sample In Research

What are the Key Steps Involved in the Sampling Process?

The sampling process comprises numerous imperative steps to ensure the representativeness of the selected sample about the population and the reliability of the gathered data. Moving forward, here we have outlined the crucial steps in the sampling process so that you will be able to understand the key steps and complete your dissertation like a professional academic writer who provides top-notch dissertation writing services.

1. Define the Population

Straightforwardly define the population of interest that the research aims to study. Nevertheless, this could be a particular group of people, items, or observations with common features.

2. Determine the Sampling Frame

Recognised the list or source from which the sample will be drawn. Furthermore, the sampling frame should include all components of the population and should be accessible for sampling.

3. Choose a Sampling Method

Select an appropriate sampling method based on the research objectives, population characteristics, and available resources. Likewise, typical sampling methods encompass random, cluster sampling, stratified and convenience sampling.

4. Determine Sample Size

In population vs sample, determining sample size is the best way to get an accurate sample size per the requirement to achieve the desired level of confidence and precision for the study. Sample size calculations often consider components such as the population size, desired margin of error and variability.

5. Select the Sample

Select the sample from the sampling frame using the chosen sampling method. Furthermore, make sure that the sampling method is randomly selected or systematic to minimise bias and make sure representativeness.

6. Obtain Informed Consent

If the research involves human subjects, obtain informed consent from participants before gathering accurate data. Inform participants about the objective of the study, their rights, and any benefits or potential risks involved. 

7. Collect Data

Once the sample is selected while studying briefly about sample vs. population in dissertation, gather data from the sampled individuals, observations, or items using accurate data collection techniques such as interviews, measurements, surveys, or observations.

8. Analyse Data

Study the collected data using suitable statistical methods and techniques. Therefore, ensure the analysis accounts for any sampling design or weighting components to obtain appropriate estimates and make valid inferences about the population.

Tabular Form Of Key Differences Between Population Vs Sample

Data are alphanumeric representations of statistical data variables, both qualitative and quantitative. Moreover, the data are those components that allow statistical inference to be made to know the actual causes and make the predictions. With the appropriate statistical data, the major differences we will explain to you are closely related: Population vs sample.





The research strives to study the entire group of individuals, items, or adherence.

A subset of individuals, items, or observations selected from the population for study.


Typically larger, comprising all elements of interest within a defined group.

Smaller, illustrating a part of the population.


Consists of every member or element of the group.

It represents a proportion or subset of the population.


The target of generalisation in research is where conclusions are drawn.

Used to make inferences about the larger population.

Data Collection

It may involve various methods depending on the research goals and resources available.

It is typically collected through sampling methods such as random sampling, stratified sampling, or convenience sampling.


The analysis is a crucial step that aims to deeply understand the group's characteristics, trends, and patterns, providing valuable insights for further research.

The analysis focuses on making inferences about the population based on the characteristics of the sample.

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About the Author

Jess Healy

Jess Healy is a dissertation writing professional who began with guest lectures at the universities in Manchester in 2011. He specialises in several fields such as literature, linguistics, creative writing and semantics. With his passion for learning and reading, he received the “Best Researcher of the Year” award in 2017. He believes in his values and is committed to boosting student success inside and outside the educational institutions. Jess joined My Assignment Services in 2014 and is now leading two of the company’s major projects.


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