A “population” in research refers to the entire group of individuals, objects, or events that a researcher intends to study and to which the study’s findings are meant to apply. It represents the complete set of elements sharing common characteristics relevant to the research question. Defining this group precisely is a foundational step in research design, influencing all subsequent stages of a study.
Understanding “Population” in Research
In research, a population is the complete collection of all units—whether individuals, objects, or occurrences—that share a specific characteristic or set of characteristics relevant to a particular investigation. This group is the ultimate focus of the study, and researchers aim to draw conclusions that describe or explain phenomena within this entire collective. For example, if a study investigates the effectiveness of a new teaching method, the population might consist of all elementary school students within a specific district or country. Researchers aim to understand this larger group, even if they cannot directly interact with every single member.
The definition of a population extends beyond just people; it can encompass anything a researcher wishes to study, such as organizations, events, countries, or even specific types of cells. For instance, a study on advertising effectiveness might define its population as all advertisements for IT jobs in a certain region during a particular period. The shared traits among members of a population are what bind them together, making them a coherent group for study purposes.
Target and Accessible Populations
Researchers distinguish between a target population and an accessible population. The target population, sometimes called the theoretical population, is the broad group to which researchers ultimately wish to generalize findings. This group meets specific criteria defined by the research question, encompassing all potential subjects regardless of how difficult they are to reach. For example, a target population might be “all individuals globally diagnosed with Type 2 diabetes.”
The accessible population is the subset of the target population a researcher can realistically reach or recruit. This group consists of individuals who meet inclusion criteria and are available for participation, often constrained by geographical location, time, or resources. Using the diabetes example, the accessible population might be “individuals diagnosed with Type 2 diabetes receiving treatment at specific hospitals within a particular city.” Study participants are drawn from this accessible group.
Population Versus Sample
The distinction between a population and a sample is fundamental in research. A population encompasses the entire group a researcher wants to draw conclusions about. Conversely, a sample is a smaller, manageable subgroup selected from this larger population. Researchers use samples because studying an entire population is often impractical, costly, or impossible due to its size. For instance, surveying every adult in a country is unfeasible.
The primary goal of using a sample is to gather data efficiently and make inferences or generalizations about the characteristics of the entire population. To achieve this, the sample must accurately reflect the diversity and attributes of the population from which it was drawn. A well-chosen sample allows researchers to draw conclusions that apply beyond the specific individuals studied. The relationship is often analogized as an aquarium (sample) representing the ocean (population).
Why Defining Your Population Matters
Precisely defining the research population is a foundational step for a study’s relevance and integrity. A clearly articulated population ensures the research question is well-focused and the study’s scope is bounded. This clarity guides the entire research process, from designing data collection instruments to selecting analytical methods. It dictates who should be included and excluded.
A well-defined population also influences the generalizability and validity of research findings. Generalizability refers to the extent results can be applied to the broader group of interest. If the population is ill-defined, or the sample does not adequately represent it, conclusions may be misleading or limited to a narrow context. Clearly outlining the population ensures research contributes meaningful and applicable insights.