Research Methods: Sampling and Population

Sampling

• Researchers use sampling to study a small portion of a large population to make estimates about the entire group.

Types of Sampling

• Probability Sampling: Involves random selection, where every individual has an equal chance of being chosen.
• Non-Probability Sampling: Involves non-random selection, where not every individual has an equal chance of being chosen.

Probability Sampling Methods

• Simple Random Sampling: A basic method where each member of the population has an equal chance of being selected.
• Stratified Sampling: Divide the population into subgroups (strata) based on shared characteristics, then randomly sample each subgroup.
  • Useful when the population has diverse subgroups that need to be represented.
• Systematic Sampling: Select members of the population at a regular interval (e.g., every 15th person on a list).
• Cluster Sampling: Divide the population into subgroups, then randomly select entire subgroups.

Non-Probability Sampling Methods

• Convenience Sampling: Select individuals who are most accessible to the researcher.
  • Example: Surveying fellow students in classes.
• Voluntary Response Sampling: People volunteer to participate (e.g., responding to an online survey).
  • May not be representative of the entire population, as participants are self-selected.

Sampling Methods

• Researchers use sampling to study a smaller portion of a larger population, making it easier to conduct accurate studies.
• Sampling allows researchers to make estimates of the larger population by studying characteristics of the small group.

Types of Sampling Methods

• Probability Sampling: involves random selection, where every individual has a chance of being included.
• Non-Probability Sampling: involves non-random selection based on convenience or other criteria, where not every individual has a chance of being included.

Probability Sampling Methods

• Simple Random Sampling: each sample has an equal probability of being chosen, and each member of the subset carries an equal opportunity of being chosen.
• Stratified Sampling: researchers divide subjects into subgroups based on characteristics, and then randomly sample each subgroup to ensure representation of all groups.
• Systematic Sampling: researchers select members of the population at a regular interval, such as selecting every 15th person on a list.
• Cluster Sampling: involves dividing the population into subgroups, and then randomly selecting entire subgroups instead of individuals.

Non-Probability Sampling Methods

• Convenience Sampling: includes individuals who are most accessible to the researcher, but may not be representative of the entire population.
• Voluntary Response Sampling: people volunteer themselves, but may not be representative of the entire population, as they may have strong opinions on the topic.