How is sample related to a population?

In the methodology section of your dissertation you will be required to provide details about both the population and sample of your study. These sections are a common stumbling block for many students, as students often fail to properly distinguish between the two. So, what exactly is the difference between the population and sample?

First, your sample is the group of individuals who actually participate in your study. These are the individuals who you end up interviewing (e.g., in a qualitative study) or who actually complete your survey (e.g., in a quantitative study). People who could have been participants in your study but did not actually participate are not considered part of your sample. For example, say you e-mailed study invitations to 200 people on a listserv and 100 of them end up participating in your study (i.e., complete your survey or your experiment). Your sample is the 100 individuals who participated in your study. The 100 individuals who received invitations but did not participate would not be considered part of your sample; rather, they are part of what is often called the sampling frame. Your sampling frame is the group of individuals who could possibly be in your study, which in the above example would be the 200 individuals on the e-mail listserv.

Discover How We Assist to Edit Your Dissertation Chapters

Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services.

• Bring dissertation editing expertise to chapters 1-5 in timely manner.
• Track all changes, then work with you to bring about scholarly writing.
• Ongoing support to address committee feedback, reducing revisions.

On the other hand, your population is the broader group of people to whom you intend to generalize the results of your study. Your sample will always be a subset of your population. Your exact population will depend on the scope of your study. For instance, say your research question asks if there is an association between emotional intelligence and job satisfaction in nurses. In this case, your population might be nurses in the United States. However, if the scope of your study is more narrow (e.g., if your study deals with a local problem or a specific specialty/industry), then your population would be more specific, such as “nurses in the state of Florida” or “licensed practical nurses in the United States.” Importantly, your population should only include people to whom your results will apply. For example, if you do not have good reason to believe that your results will apply to all nurses in the United States, then your population will need to be more specific. If you are stuck on defining your population, think about how you would fill in the blank in the following sentence: “The results of my study will apply to _____.” Your answer will help determine how you define your population.

To summarize: your sample is the group of individuals who participate in your study, and your population is the broader group of people to whom your results will apply. As an analogy, you can think of your sample as an aquarium and your population as the ocean. Your sample is small portion of a vaster ocean that you are attempting to understand. Properly distinguishing between these two concepts will aid you as you navigate the methodological details of your dissertation.

In market research and statistics, every study has an essential inquiry at hand. Observation and experiment of a sample of the population determine the result of this inquiry. It is done to derive insights that explain a phenomenon within the whole population.

Select your respondents

What is the ‘population’ in market research?

Definition: Population in research is a complete set of elements that possess a standard parameter between them.

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

The ‘population’ in research doesn’t necessarily have to be human. It can be any parameter of data that possesses a common trait.

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

What is a sample in market research?

Definition:  A sample is a 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 said, a sample is a subgroup or subset within the population. This sample can be studied 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 kind 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 characteristics are studied. The results are 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.

Here are the most common sampling techniques:

Sampling techniques are broadly classified as two types:
Probability sampling and non-probability sampling.

1. Probability sampling – Samples chosen based on the theory of probability.
   a. Simple random sampling
   b. Cluster sampling
   c. Systematic sampling
   d. Stratified random sampling
2. Non-Probability sampling – Samples chosen based on the researcher’s subjective judgment.
   a. Convenience sampling
   b. Judgemental or Purposive sampling
   c. Snowball sampling
   d. Quota sampling

How to choose high-quality samples:

Although we make sure that all the members of a population have an equal chance to be included in the sample, it does not mean that the samples derived from a particular population and satisfying the criterion will be alike. They will still vary from one another. This variation can be slight or substantial.

For example, a set of samples of healthy people’s body temperature will show a very less difference. But the difference in these people’s systolic blood pressure would be sizeable.

It is also observed that the accuracy of the data depends on the size of the sample. The accuracy is much lesser with a smaller sample size compared to using a larger sample for the study. Thus, if two, three or more samples are derived from a population, the bigger they are, the more they tend to resemble each other.

Population vs Sample – top seven reasons to choose a sample from a given population

Sampling is a must to conduct any research study. Here are the top seven reasons to use a sample:

• Practicality: In most cases, a population can be too large to collect accurate data – which is not practical. Samples offer a representation of the whole population if sampled accordingly. Samples allow researchers to collect data that can be analyzed to provide insights into the entire 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 provides a smaller set of the population for review, that delivers data that is useful to represent the whole population. Surveying a smaller sample, as opposed to the entire population, can save precious time for researchers and offer urgent data.

• 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, to carry out a survey and gain accurate insights. Surveying a representative sample of a population is cost-effective as it requires fewer resources – like computers, researchers, interviewers, servers, and data collection centers.

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

• Inferential statistics: Inferential statistics is a process by which representative data is used to infer insights about the entire population. Data collected from a sample represents the whole population. Inferential statistics can only be obtained 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 sampling bias and provides more accurate data – that adequately represents the population.

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

Select your respondents

Population vs Sample – What is the difference?

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:

Population

Sample

Although Population and Sample are two different terms, they both are related to each other. The population is used to draw samples. To make statistical inferences about the population is the primary purpose of the sample. Without the population, samples can’t exist. The better the quality of the sample, the higher the level of accuracy of generalization.

How is a sample related to a population quizlet?

Why is a sample used more often than population?

What is the relation between a sample and a population of interest?

How is a sample used to make conclusions about the population?