Population & its Types

Population refers to the entire group of individuals or objects that share a common characteristic and are of interest to a researcher.

Population in Statistics & its Types

Population refers to the entire group of individuals or objects that share a common characteristic and are of interest to a researcher. In research studies, populations are typically defined based on certain criteria or attributes that are relevant to the research question. The choice of population is crucial as it determines the generalizability of the findings to the target group.


A population parameter is a numerical value that represents a specific characteristic of an entire population. Parameters are derived from data collected from the entire population and can include measures such as the mean or standard deviation. These statistics provide valuable insights into the population’s characteristics. Parameters, denoted by Greek letters such as µ (mu) for the population mean and σ (sigma) for the population standard deviation, are typically unknown and are estimated from sample data.

For instance, consider the population of all students in a school. The population parameter for the mean height of these students would provide an accurate measure of the average height across the entire population. Similarly, the population parameter for the standard deviation would reflect the level of variability in height within the population.

It is important to differentiate population parameters from sample statistics. Sample statistics, such as sample means or sample standard deviations, are calculated from a subset of the population, known as a sample. These statistics provide estimates of the population parameters but may vary due to the inherent variability present in different samples.

Common Types of Population in Statistics

Different types of populations exist in research, and understanding them is essential for sampling, data collection, and drawing valid conclusions. Here are some commonly encountered population types:

Finite Population: A finite population, also known as a countable population, consists of individuals or objects that can be counted. Statistical analysis of finite populations is advantageous compared to infinite populations. Examples include number of elementary school teachers employed in public sector or number of students appeared in SSC exams.

Infinite Population: An infinite population, also known as an uncountable population, consists of units that cannot be counted. For instance, the number of germs in a patient’s body is uncountable. Other examples of infinite populations are stars in the sky or trees on Earth.

Existent (real) Population: An existent population comprises concrete individuals or units that are available in solid form. Since, these populations refer to units that exist in real form. They are also called real populations. Examples include books on certain topic or students in a class.

Hypothetical Population: It is just the opposite of the existent population. A hypothetical population consists of units that are not available in solid form. They may represent sets of observations or objects that are abstract or theoretical and have something in common. Examples include the outcome of rolling a dice or tossing a coin.

Homogeneous Population: A homogeneous population is one in which all individuals or objects share the same nature or characteristics. For instance, a population composed of students of the same age group, same height, or same grade would be considered homogeneous.

Heterogeneous Population: A heterogeneous population is one in which individuals or objects have different natures or characteristics. Examples include a group of students with different races or a group of books with various topics.

Important Types of Research Population

In research, two important population types are the target population and the accessible population:

Target Population (Universe): The target population is the specific group of individuals or objects that researchers wish to study and make inferences about. It represents the entire group to which the study findings will be generalized. For example, the target population for a study on reading habits of 8th graders might be all the students enrolled in grade 8th in a particular state/province.

Accessible Population: The accessible population refers to the subset of the target population that the researcher can access for data collection. Due to logistical constraints or limited resources, studying the entire target population may be impractical. Therefore, researchers select an accessible population that is representative of the target population to ensure valid inferences. The accessible population may be limited to a specific region, city, gender, or institution. This is the population from which the researcher selects sample of the study.

Understanding the different types of populations and their distinctions is essential for researchers to appropriately define their study population, select appropriate sampling techniques, and draw valid conclusions from their research.


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