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What is the main advantage of using simple random sampling?
What is the main advantage of using simple random sampling?
When is simple random sampling preferred?
When is simple random sampling preferred?
What defines systematic random sampling?
What defines systematic random sampling?
What is the first step in obtaining a systematic random sample?
What is the first step in obtaining a systematic random sample?
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Which of the following is a disadvantage of simple random sampling?
Which of the following is a disadvantage of simple random sampling?
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What is a common drawback of systematic random sampling?
What is a common drawback of systematic random sampling?
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What is represented by the variable 'k' in systematic random sampling?
What is represented by the variable 'k' in systematic random sampling?
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Which sampling technique assigns equal probabilities of selection to each possible sample?
Which sampling technique assigns equal probabilities of selection to each possible sample?
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What is the definition of a target population?
What is the definition of a target population?
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What is an observation unit in statistical studies?
What is an observation unit in statistical studies?
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Why is it important for a sample to be representative?
Why is it important for a sample to be representative?
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Which option correctly defines 'biased sampling'?
Which option correctly defines 'biased sampling'?
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What is a sampling frame?
What is a sampling frame?
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What is a disadvantage of using a sampling method when there is unsuspected periodicity in the population?
What is a disadvantage of using a sampling method when there is unsuspected periodicity in the population?
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What does the term 'sampling unit' refer to?
What does the term 'sampling unit' refer to?
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Under which condition is it advisable to use a systematic sampling method?
Under which condition is it advisable to use a systematic sampling method?
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What is a sample in statistics?
What is a sample in statistics?
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How is the value of 'k' determined in systematic sampling when selecting from a population?
How is the value of 'k' determined in systematic sampling when selecting from a population?
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What does the term 'sampling technique' refer to?
What does the term 'sampling technique' refer to?
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What is the purpose of stratifying a population in statistical sampling?
What is the purpose of stratifying a population in statistical sampling?
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Which of the following is NOT a requirement when using stratified sampling?
Which of the following is NOT a requirement when using stratified sampling?
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What does systematic sampling specifically involve?
What does systematic sampling specifically involve?
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Which aspect is crucial for using stratified sampling effectively?
Which aspect is crucial for using stratified sampling effectively?
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When selecting a systematic sample from a population of 500 students, with a sample size of 50, what would the value of 'k' be?
When selecting a systematic sample from a population of 500 students, with a sample size of 50, what would the value of 'k' be?
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Which sampling technique involves selecting individuals based on chance encounters?
Which sampling technique involves selecting individuals based on chance encounters?
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What is the main characteristic of Purposive Sampling?
What is the main characteristic of Purposive Sampling?
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Which sampling method is best suited when immediate reactions are needed?
Which sampling method is best suited when immediate reactions are needed?
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What type of error is defined as mistakes that arise from the survey process and are not due to sample variability?
What type of error is defined as mistakes that arise from the survey process and are not due to sample variability?
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Which of the following is NOT a source of Non-sampling Error?
Which of the following is NOT a source of Non-sampling Error?
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When is Non-Probability Sampling particularly useful?
When is Non-Probability Sampling particularly useful?
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Which sampling technique relies on the judgment of an expert to select participants?
Which sampling technique relies on the judgment of an expert to select participants?
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What is a common characteristic of Sampling Errors?
What is a common characteristic of Sampling Errors?
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What is undercoverage in the context of sampling?
What is undercoverage in the context of sampling?
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Which of the following describes probability sampling?
Which of the following describes probability sampling?
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What is a key disadvantage of non-probability sampling?
What is a key disadvantage of non-probability sampling?
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What can result from allowing the sample to consist entirely of volunteers?
What can result from allowing the sample to consist entirely of volunteers?
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What is a common advantage of using sampling instead of complete enumeration?
What is a common advantage of using sampling instead of complete enumeration?
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Which step is NOT part of the sampling procedure?
Which step is NOT part of the sampling procedure?
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How does failing to obtain responses from all of a chosen sample affect the results?
How does failing to obtain responses from all of a chosen sample affect the results?
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What issue arises from having multiple listings in the sampling frame?
What issue arises from having multiple listings in the sampling frame?
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Study Notes
Probability Sampling
- Probability sampling is a sampling technique that uses a random method to select individuals, ensuring each member of the population has a known chance of being selected.
- It is referred to as random sampling and allows for generalizations about the population based on the collected data.
- Common Probability Sampling techniques include:
- Simple Random Sampling
- Systematic Random Sampling
- Stratified Sampling
- Cluster Sampling
- Multi-stage Sampling
Simple Random Sampling
- This technique assigns equal probabilities of selection to each member of the population.
- It is easy to use but might be less effective if the population is geographically spread out or heterogeneous.
- It is ideal for populations that are homogeneous and don't have a wide geographical distribution.
Systematic Random Sampling
- This technique selects every kth individual from a population, where k is calculated by dividing the population size by the desired sample size.
- It is simple and easy to administer, offering advantages in terms of efficiency.
- It can be less precise if the population has a hidden periodicity, which could lead to biased selection.
- It is suitable if the ordering of the population is considered essentially random.
Stratified Sampling
- This technique divides the population into subgroups called strata, where individuals within each stratum share similar characteristics.
- A simple random sample is then drawn from each stratum.
- This technique is beneficial when information about the population is available and can be used to form strata.
- It is helpful when the population is diverse, ensuring that all subgroups are adequately represented in the sample.
Cluster Sampling
- This technique involves dividing the population into clusters and randomly selecting clusters for sampling.
- It is convenient when dealing with large populations that are geographically spread out.
- It is especially suitable when it is impractical to obtain a complete list of all individuals.
Multi-stage Sampling
- This technique combines different sampling methods in multiple stages.
- For example, it might start with cluster sampling and then use simple random sampling within the selected clusters.
- This approach is useful for handling complex population structures and can increase the efficiency of sampling.
Non-Probability Sampling
- This technique uses non-random selection methods, making it difficult to generalize population findings from the sample.
- It should not be used for statistical inference.
- It is often used in situations where probability sampling is not feasible or cost-effective.
- Common Non-probability Sampling techniques include:
- Accidental Sampling
- Quota Sampling
- Convenience Sampling
- Purposive Sampling
- Judgement Sampling
Accidental Sampling
- This technique involves selecting individuals who are readily available or encountered by chance.
- It lacks control and can lead to biased results.
Quota Sampling
- This technique involves selecting individuals based on pre-determined quotas based on specific characteristics like gender, age, or socioeconomic status.
- It seeks to ensure representation of various groups, but might result in selective bias.
Convenience Sampling
- This technique selects individuals who are easily accessible to the researcher, often based on convenience or availability.
- It faces the risk of being highly biased and not representative of the population.
Purposive Sampling
- This technique selects individuals based on specific criteria determined by the researcher.
- It is useful for selecting individuals with specific expertise or experiences, but it can be subjective.
Judgement Sampling
- This technique selects individuals based on the researcher's judgment, often relying on experts or knowledgeable individuals within the field.
- It is prone to bias, as the selection reflects the researcher's personal opinions.
Advantages of Sampling over Complete Enumeration (Census)
- Reduced Labor: Sampling requires less effort than collecting data from the entire population.
- Reduced Cost: Sampling costs are generally lower than conducting a complete census.
- Greater Speed: Sampling allows for faster data collection and analysis.
- Greater Scope: Sampling can study larger and more diverse populations that might be impossible to cover in a census.
- Greater Efficiency: Sampling can provide more focused and accurate data for a specific research question.
- Convenience: Sampling is often more practical and convenient for data collection.
- Ethical Considerations: Sampling might be ethically necessary in situations where collecting complete data from the population would be harmful.
Bias Selection
- It refers to systematic errors in the sampling process that lead to non-representative samples.
- Types of bias include:
- Deliberately selecting a "representative" sample based on subjective judgments.
- Failing to define the target population clearly.
- Undercoverage: Failing to include all members of the target population in the sampling frame.
- Overcoverage: Including individuals in the sampling frame who are not part of the target population.
- Multiplicity of Listings: Having multiple entries of the same individual in the sampling frame.
- Substitution: Replacing a designated individual with a convenient alternative.
- Nonresponse: Failing to obtain responses from all individuals in the selected sample.
- Volunteer Sampling: Allowing the sample to consist entirely of volunteers.
Sources of Errors in Sampling
- Non-sampling Error: These are errors that occur during the survey process, unrelated to the selection of the sample. These errors can be attributed to various factors such as:
- Non-response
- Interviewer error
- Misrepresented answers
- Data Entry Errors
- Sampling Error: These are errors that arise from the fact that a sample is used to represent the population. Statistical techniques are used to estimate the magnitude of the error.
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Description
This quiz explores various probability sampling techniques such as Simple Random Sampling, Systematic Random Sampling, and others. Understand the principles behind selecting samples and the advantages of different methods. Test your knowledge on how these techniques are implemented in research.
