Podcast Beta
Questions and Answers
What type of sampling allows strong statistical inferences about the whole group?
In which type of sampling are individuals selected based on convenience or other criteria?
What is the characteristic of Snowball Sampling?
Which sampling method involves dividing the population into subgroups before sampling?
Signup and view all the answers
What is the distinguishing feature of Purposive Sampling?
Signup and view all the answers
Study Notes
Probability Sampling
- Allows strong statistical inferences about the whole group
- Involves random selection of participants
- Examples include:
- Simple Random Sampling: each participant has an equal chance of being chosen
- Systematic Sampling: select every nth individual from a list
- Stratified Sampling: divide the population into subgroups (strata) and sample from each
- Cluster Sampling: randomly select clusters (e.g., schools, neighborhoods) and sample all individuals within those clusters
Non-Probability Sampling
- Based on convenience or other criteria, rather than random selection
- Examples include:
- Convenience Sampling: conveniently select available participants
- Purposive Sampling: handpick participants based on specific characteristics
- Snowball Sampling: start with a few participants and ask them to refer others
- Quota Sampling: set quotas for different subgroups and sample accordingly
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Learn about different types of sampling techniques used in statistics, including probability sampling methods like Simple Random Sampling, Systematic Sampling, Stratified Sampling, and Cluster Sampling. Understand the differences between probability and non-probability sampling approaches.
