Research Methods: Types of Sampling

A sampling method where every member of the population has a chance of being selected.

The specific group of people you want to study, defined by characteristics like location, age, and income.

Research that uses numbers and statistical analysis to understand a topic.

An international song competition.

College students.

The entire group you're interested in studying.

Selecting a smaller group from a larger population.

Specify the group you want for a study.

A population is the entire group being studied, while a sample is a smaller, selected subgroup used for data collection.

A sampling method where the chance of being selected isn't known, often based on convenience.

A sample that accurately reflects the characteristics of the larger population.

Group of people who will participate in a research study.

Conclusions drawn from research that are accurate and reliable based on a representative research sample.

Every member of the population has an equal chance of being selected.

Individuals are selected from a list at regular intervals.

The population is divided into subgroups and a sample is taken from each.

Entire subgroups are randomly selected, rather than individuals from each subgroup.

Researchers choose participants based on specific characteristics relevant to the study.

Simple random sampling randomly selects participants, while systematic sampling selects participants at regular intervals from a list.

Stratified sampling ensures that subgroups within the population are represented in the sample, leading to more accurate and precise results.

Cluster sampling is useful when the population is naturally divided into groups, and studying all individuals in those groups is practical and efficient.

Choosing participants who are readily available, often based on ease of access.

Researchers use their expertise to select a sample they believe is most relevant to their research goals.

Participants self-select by choosing to participate, usually by responding to a public request.

Recruiting participants through existing participants, reaching a wider network.

Convenience samples often lack representativeness, meaning the results may not accurately reflect the entire population due to bias.

People who volunteer for surveys or studies may have different opinions or characteristics than those who don't, skewing the results.

Non-probability sampling methods are prone to bias, making it difficult to generalize findings to the entire population.

Snowball sampling is useful when the target population is hard to reach or identify, allowing researchers to access the target population through referrals.