*Sampling Methods Flashcards
What is Simple Random Sampling?
Every member of the population has an equal chance of being selected (uses sampling frame)
Strengths: High representativeness; minimizes bias. Weaknesses: Requires a complete list of the population; not always practical.
What are the strengths of Simple Random Sampling?
High representativeness; minimizes bias
It ensures that every individual has an equal opportunity to be selected.
What are the weaknesses of Simple Random Sampling?
Requires a complete list of the population; not always practical
This can be a barrier in cases where a full population list isn’t available.
What is Systematic Sampling?
Selection of every nth individual from a list or sequence (uses sampling frame)
This method simplifies the random sampling process.
What are the strengths of Systematic Sampling?
Simpler than random sampling; ensures coverage across the population
It provides a straightforward approach to selecting samples.
What are the weaknesses of Systematic Sampling?
Risk of periodicity bias; requires a list
If the list has a hidden pattern, it could skew results.
What is Stratified Sampling?
Population divided into subgroups (strata) that are meaningful to the research question; random samples taken from each stratum
This method enhances the representativeness of significant subgroups.
What are the strengths of Stratified Sampling?
Enhances representativeness of significant subgroups
It ensures that all relevant segments of the population are included.
What are the weaknesses of Stratified Sampling?
Requires detailed population information; more complex to organise
The complexity can make it challenging to implement.
What is Cluster Sampling?
Population divided into clusters; a random sample of clusters is selected and all or a random sample of members from chosen clusters are surveyed (needs sampling frame)
This method is often used for geographically dispersed populations.
What are the strengths of Cluster Sampling?
Cost-effective for large, geographically dispersed populations
It reduces costs associated with surveying a wide area.
What are the weaknesses of Cluster Sampling?
More variance than simple random sampling; clusters may not be homogeneous
This can lead to less reliable results compared to other methods.
What is Convenience Sampling?
Sampling based on availability and willingness to participate (no sampling frame needed)
This method is often used in exploratory research.
What are the strengths of Convenience Sampling?
Easy and inexpensive
It allows researchers to gather data quickly.
What are the weaknesses of Convenience Sampling?
High risk of bias; not representative
The sample may not reflect the larger population.
What is Snowball Sampling?
Participants recruit other participants among their acquaintances
This method is useful for reaching hidden or hard-to-reach populations.
What are the strengths of Snowball Sampling?
Useful for reaching hidden or hard-to-reach populations
It leverages existing social networks to find participants.
What are the weaknesses of Snowball Sampling?
Potential for high bias; not representative
The sample may be biased towards certain social networks.
What is Purposive Sampling?
Selection based on specific characteristics or qualities; researchers’ judgment
This method targets relevant participants for qualitative research.
What are the strengths of Purposive Sampling?
Targets relevant participants for qualitative research
It allows researchers to focus on specific traits or experiences.
What are the weaknesses of Purposive Sampling?
Subjective; potential for bias
The researcher’s judgment can influence the sample selection.
What is Quota Sampling?
Ensures representation of specific characteristics in the sample to match their proportions in the population
This method aims to ensure diversity within the sample.
What are the strengths of Quota Sampling?
More controlled than convenience sampling; ensures diversity
It helps in making sure that different segments of the population are represented.
What are the weaknesses of Quota Sampling?
Non-random; potential for selection bias
This can lead to skewed results if not carefully managed.
