16 Questions
What is the primary reason for using systematic sampling over simple random sampling?
To avoid data manipulation and maintain low risk
When is stratified random sampling most suitable to use?
When the group is heterogeneous and there is a need to avoid bias
What is the main purpose of stratified random sampling?
To ensure proportional representation of each stratum
Why is cluster sampling most suitable for populations spread out over a wide area?
When it is difficult to access individual members of the population
What does systematic sampling aim to minimize?
Data manipulation and risk
Why is it important for researchers to determine the characteristics of the population before using stratified random sampling?
To obtain appropriate divisions needed in the problem
What is the main reason for researchers to choose quota sampling?
To sample a subgroup that is of great interest to the study
Which sampling technique relies on the researcher's own judgment when choosing members of the population to participate in the study?
Purposive sampling
What is the primary objective of convenience sampling?
To be done with comfort as its prime objective
In which type of sampling is data collected from a homogeneous group with a limited number of samples in proportion to some characteristic or trait of a population?
Quota sampling
Which type of sampling method does not require that a simple random sample is generated?
Convenience sampling
When do researchers use purposive sampling?
When they want to access a particular subset of people
What characterizes probability or random sampling?
Selecting sample size from population such that each member has an equal chance of being included
What is the main reason for not examining every member of the population in a research study?
Due to cost and time constraints
What does non-probability or non-random sampling techniques include?
Quota, purposive, and convenience sampling techniques
What defines purposive sampling?
A type of non-probability sampling method where data is collected according to the purpose.
Study Notes
Sampling Techniques
- Systematic sampling is used to minimize sampling bias and ensure representation of the population.
- Stratified random sampling is most suitable when the population is heterogeneous and can be divided into distinct subgroups.
Stratified Random Sampling
- The main purpose of stratified random sampling is to ensure that the sample is representative of the population by accounting for the differences between subgroups.
- Researchers must determine the characteristics of the population before using stratified random sampling to ensure that the subgroups are accurately identified.
Cluster Sampling
- Cluster sampling is most suitable for populations spread out over a wide area, as it involves selecting groups or clusters of participants rather than individual participants.
Systematic Sampling
- Systematic sampling aims to minimize sampling bias by selecting every nth participant from the population.
Quota Sampling
- The main reason for researchers to choose quota sampling is to ensure that the sample contains a certain proportion of participants with specific characteristics.
Non-Probability Sampling
- Convenience sampling is a type of non-probability sampling that relies on the researcher's own judgment when choosing members of the population to participate in the study.
- The primary objective of convenience sampling is to gather data quickly and easily, often using participants who are readily available.
- Purposive sampling is a type of non-probability sampling that involves selecting participants based on their expertise or knowledge in a specific area.
- Researchers use purposive sampling when they need to gather in-depth information from a small group of experts or individuals with specific characteristics.
- Non-probability or non-random sampling techniques include quota sampling, convenience sampling, and purposive sampling.
Probability Sampling
- Probability or random sampling is characterized by the use of random selection methods to ensure that every participant in the population has an equal chance of being selected.
- The main reason for not examining every member of the population in a research study is that it is often impractical or impossible due to time, cost, or logistical constraints.
Sampling Definitions
- Purposive sampling is defined by the selection of participants based on their expertise or knowledge in a specific area.
- Cluster sampling is a type of probability sampling that involves selecting groups or clusters of participants rather than individual participants.
Explore the concepts of sampling techniques in statistics, quality assurance, and survey methodology. Learn about the advantages of systematic sampling over simple random sampling and the risks associated with data manipulation.
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