38 Questions
What is the purpose of quotas in a study?
To ensure a proportional representation of the population
What is the advantage of using quotas in a study?
It helps ensure a diverse sample
What is the research method described in the content?
Quota sampling
Why is it better for participants to come forward themselves?
For ethical reasons
What is the population distribution in the example?
60% Democrat, 35% Republican, 5% Independent
What is the sample size required in the example?
200 adults
What is the purpose of collecting data in a business setting?
To understand customer needs and improve the business
What is the age range of the students targeted by the teacher in the example?
9-11 years old
What is the limitation of the collection of data from friends and family?
It is biased and based on a small, non-representative sample
How many sampling techniques are under Probability Sampling?
5
What is the characteristic of Simple Random Sampling?
Each population case has equal presence amount of probability in a sample
What is the main difference between Probability and Non-Probability Sampling?
The probability of selection
What is the advantage of collecting primary data in a business setting?
It is more specific to the business's needs
What is the limitation of using a small sample size?
It may not be representative of the larger population
Why is stratified sampling preferred over simple random sampling?
Because it warrants extra precise statistical results
What is a disadvantage of simple random sampling?
The costs of obtaining the sample can be high.
What is an advantage of systematic sampling?
It is simpler to implement than simple random sampling.
What is the main reason to use cluster sampling?
When the population is too large to perform simple random sampling
What is the key difference between stratified sampling and cluster sampling?
Stratified sampling involves dividing the population into subgroups, while cluster sampling involves dividing the population into clusters
What is a strength of stratified random sampling?
It is very precise.
What is the purpose of identifying boundaries in cluster sampling?
To ensure each cluster has an equal opportunity of being selected
What is a weakness of simple random sampling?
It has a sampling frame that is difficult to construct.
What is the next step in cluster sampling after identifying the clusters?
Selecting a simple random sample of many clusters
What is a characteristic of systematic sampling?
Every nth individual in the population is selected.
What is true about the areas selected in cluster sampling?
They are selected randomly and have an equal opportunity of being selected
What is a weakness of stratified random sampling?
It is impossible to stratify on many variables.
What is the advantage of using stratified sampling over simple random sampling?
It provides more precise statistical results
What is an advantage of simple random sampling?
It provides projectable results.
What is a characteristic of stratified random sampling?
It involves splitting the population into subgroups.
What is the main difference between stratified sampling and multistage sampling?
Stratified sampling is a single-stage process, while multistage sampling is a multi-stage process
What is the primary purpose of sampling in research?
To select a subset of the population for study
What is the main characteristic of probability sampling?
Every member of the population has an equal chance of being selected
What is the process used to remove biases in probability sampling?
Randomization
What is the primary difference between probability and non-probability sampling?
The chance of each member being selected
Which of the following is an example of probability sampling?
Selecting a random sample from a box of balloons with different colors
What is the main characteristic of non-probability sampling?
Not every member of the population has an equal chance of being selected
Which of the following is an example of non-probability sampling?
Selecting children affected by HIV/AIDS for a study
What is the purpose of randomization in probability sampling?
To remove biases in sampling
Study Notes
Defining Sampling
- Sampling is a method to select a sample from a large population or individual group for a specific research target.
- It consists of two main techniques: Probability Sampling and Non-Probability Sampling.
Differentiating between Probability and Non-Probability Sampling
- Probability Sampling: Every item in the population has an equal chance of being selected in the sample.
- Non-Probability Sampling: Each member of the population sample is not aware of the chances of being selected.
Methods of Probability Sampling
-
Simple Random Sampling: Each population case has an equal probability of being selected in the sample.
- Strengths: easily understood, provides projectable results
- Weaknesses: difficult to construct a sampling frame, expensive, low precision, no assurance of representativeness
-
Systematic Sampling: Every unspecified number after a random start is chosen.
- Strengths: easy to implement, can be done without a frame, increases representativeness
- Weakness: can decrease representativeness
-
Stratified Random Sampling: The population is split into subgroups, and a random sample is taken from each subgroup.
- Strengths: precise, includes all important subpopulations
- Weaknesses: expensive, impossible to stratify on many variables, challenging to select relevant stratification variables
- Cluster Sampling: Divides the population into groups or clusters, and a simple random sample is taken from each cluster.
- Multistage Sampling: Selects a sample in multiple stages, using different sampling techniques at each stage.
Non-Probability Sampling
- Quota Sampling: A non-probability sampling technique where the researcher selects the sample based on predetermined quotas.
- Convenience Sampling: A non-probability sampling technique where the researcher uses easily accessible individuals, such as friends and family.
Key Concepts
- Sampling Bias: Systematic error in the sampling process that can affect the representativeness of the sample.
- Stratification: Dividing the population into subgroups to ensure adequate representation in the sample.
- Randomization: A process used to reduce bias and ensure equal probability of selection in the sample.
This quiz tests your understanding of stratified sampling in research methodology, including setting non-overlapping strata and studying specific subgroups within a population.
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