Sampling Basics and Considerations
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Sampling Basics and Considerations

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What is a sample in the context of research?

  • A list of all possible participants in the study
  • A smaller collection of units used to determine truths about a population (correct)
  • The entire population from which data is collected
  • Random subset of unrelated individuals

    • Why is sampling important when conducting research?

  • It allows for analyzing every individual in the population
  • It ensures all data collected is precise
  • It decreases the overall effort required for research
  • It helps manage limited resources while providing results with known accuracy (correct)

    • Which of the following factors does NOT influence sample representativeness?

  • Researcher bias (correct)
  • Participation
  • Sample Size
  • Sampling Procedure

    • What is the rule of thumb regarding sample size in research?

    <p>The larger the sample size, the better the representation</p> Signup and view all the answers

    Under what circumstances might a researcher choose to sample the entire population?

    <p>When extensive resources are available</p> Signup and view all the answers

    What happens mathematically if there are too many participants in a study?

    <p>Diminishing returns on accuracy occur</p> Signup and view all the answers

    What is a common consideration in determining the number of participants for a study?

    <p>The desired level of statistical power and representativeness</p> Signup and view all the answers

    What constitutes a possible population in research sampling?

    <p>Any defined group identifiable by certain characteristics</p> Signup and view all the answers

    What sampling method is used when surveying every fifth person on a ticket list?

    <p>Systematic</p> Signup and view all the answers

    Why is cluster sampling used to determine immunization coverage in a province?

    <p>It is easier to manage and reduces costs.</p> Signup and view all the answers

    Which sampling method is most suitable for studying women's narcissistic tendencies after laser treatments?

    <p>Purposive sampling</p> Signup and view all the answers

    Which sampling method would be optimal for determining the proportion of underpaid migrant workers in East London?

    <p>Snowball sampling</p> Signup and view all the answers

    What type of sampling is characterized by every member of a population having an equal chance of selection?

    <p>Simple random sampling</p> Signup and view all the answers

    When is stratified random sampling most appropriate?

    <p>When specific subgroups need representation.</p> Signup and view all the answers

    When can systematic sampling lead to a biased sample?

    <p>When there's a predefined order in the population.</p> Signup and view all the answers

    What method is Farmer Joe using when he estimates total apple production based on one region?

    <p>Cluster sampling</p> Signup and view all the answers

    What is a characteristic of convenience sampling?

    <p>It selects samples based on what is easily accessible to the researcher.</p> Signup and view all the answers

    Which type of sampling is directly equivalent to stratified sampling in non-probability sampling?

    <p>Quota sampling</p> Signup and view all the answers

    Which of the following statements best describes purposive sampling?

    <p>Selection is made based on the researcher's specific knowledge and objectives.</p> Signup and view all the answers

    What is one limitation of non-probability sampling methods?

    <p>They may introduce bias and do not ensure proportional representation.</p> Signup and view all the answers

    Which type of sampling is best suited for gathering a sample where the desired characteristic is rare?

    <p>Snowball sampling</p> Signup and view all the answers

    Which of the following is true about probability sampling?

    <p>Each unit has a known and equal chance of being selected.</p> Signup and view all the answers

    What distinguishes quota sampling from other non-probability methods?

    <p>It divides the population into strata and selects based on predetermined proportions.</p> Signup and view all the answers

    What is a key feature of snowball sampling?

    <p>It relies on recommendations from previously selected participants.</p> Signup and view all the answers

    What is the primary goal of stratified random sampling?

    <p>To ensure each group is represented adequately.</p> Signup and view all the answers

    In systematic random sampling, which condition is necessary for the list of participants?

    <p>The list should have no hidden order.</p> Signup and view all the answers

    Which of the following best describes cluster random sampling?

    <p>Surveying all members in a few randomly chosen clusters.</p> Signup and view all the answers

    How should the sample sizes be determined in stratified random sampling?

    <p>Sample sizes should reflect the proportion of the stratum in the population.</p> Signup and view all the answers

    What is a crucial step to follow when implementing systematic random sampling?

    <p>Establish an n value that is consistent across all participants.</p> Signup and view all the answers

    Why might stratified random sampling be preferred over simple random sampling?

    <p>It allows for specific subgroup analysis within the population.</p> Signup and view all the answers

    Which scenario is most suited for cluster random sampling?

    <p>Gathering income data across a nation without a comprehensive list.</p> Signup and view all the answers

    In a stratified random sampling example, if 400 students must be sampled, how should they be divided between two strata?

    <p>Select 200 students from public and 200 from private schools.</p> Signup and view all the answers

    What does a 95% confidence level indicate regarding survey results?

    <p>You are 95% certain that results reflect the population's opinions.</p> Signup and view all the answers

    What is the relationship between margin of error and confidence level?

    <p>Larger margins of error decrease the confidence level.</p> Signup and view all the answers

    What is typically done to correct sampling error?

    <p>Increase the sample size.</p> Signup and view all the answers

    What is sampling bias?

    <p>Collection of data from only those interested.</p> Signup and view all the answers

    Which of the following describes non-sampling error?

    <p>Errors due to low response rates.</p> Signup and view all the answers

    Which type of sampling allows every member of a population to have an equal chance of being selected?

    <p>Random sampling.</p> Signup and view all the answers

    What calculation represents the likelihood of an event occurring in probability?

    <p>A number between 0 and 1.</p> Signup and view all the answers

    Which statement best describes margin of error?

    <p>It specifies your results' precision level.</p> Signup and view all the answers

    What is a key characteristic of non-probability sampling?

    <p>Selection is solely at the researcher's discretion.</p> Signup and view all the answers

    Which factor contributes to achieving closer results to the true population size?

    <p>Larger sample sizes.</p> Signup and view all the answers

    Study Notes

    Sampling Basics

    • Sample: smaller collection of units from a population used to determine facts about the population
    • Why sample?:
      • Limited resources: Time, Money, Workload
      • Calculate accuracy: Gives results with known accuracy that can be calculated mathematically

    Considerations in Sampling

    • Confidence Level: level of certainty that your data is a true representation of the entire population. (Ex: 95% confidence level = 95% certain that the results reflect the opinions of the entire population)
    • Margin of Error: shows the uncertainty, tells you how much you can expect the results to reflect the views from the overall population. (Ex: 4% margin of error = your results are within 4 percentage points of the real population value)
    • Larger sample sizes are closer to the population size, which reduces the risk of the sample being unusual by chance.
    • The more data you have, the more capacity to draw out existing relationships between them.

    Sampling Bias and Sampling Error

    • Sampling Bias:
      • Occurs when there is over-representation or under-representation of the population.
      • Results are influenced by bias, not representative of the target population.
    • Sampling Error:
      • Results when there is sampling bias.
      • Samples are not representative of the target population.
      • Normally corrected by increasing the sample size.
    • Non-Sampling Error: Problems in data collection or processing.
      • Low response rate
      • Error in instrument in data collection (validity and reliability)
      • Mistakes in data encoding

    Sampling Techniques

    • Probability
      • Measure of the likelihood that an event will occur in a random experiment.
      • Quantified as a number between 0 and 1, where 0 = impossibility and 1 = certainty.
      • The higher the probability of an event, the more likely it is that the event will occur.
    • Probability Sampling
      • Random selection for the sample.
      • Every member of a population has a known (calculated) and equal chance of being selected.
    • Non-Probability Sampling
      • Judgment of researcher
      • The odds of any member being selected for a sample cannot be calculated.

    Types of Probability Sampling

    • Simple Random Sampling:
      • Each member of the population has a known and equal chance of being selected.
      • It's a good way to get a representative sample when you don't have information about the population that might make some individuals more likely to be selected than others.
    • Stratified Random Sampling:
      • Identify relevant stratums and action representation in the population.
      • Use random sampling to select sufficient number of subjects in each stratum.
    • Systematic Random Sampling:
      • Nth name selection technique.
      • Choose every “nth” participant from a complete list.
    • Cluster Random Sampling:
      • Obtained by dividing the study population into clusters (typically geographically).
      • Ideally, members of the clusters are homogenous/similar.
      • A cluster sample gets every member from some of the groups.

    Types of Non-Probability Sampling

    • Convenience Sampling:
      • Used in exploratory research when the researcher wants a quick and inexpensive way to get an approximation of the truth.
      • Sample is selected because it is convenient.
    • Quota Sampling:
      • Non-probability equivalent of stratified sampling.
      • Groups in the sample are proportional to the groups in the population.
      • Identify stratums and their proportions as they are represented in the population.
    • Purposive Sampling:
      • Researcher chooses a sample based on their knowledge about the population and the study itself. Usually an extension of convenience sampling.
      • Participants are chosen based on the study's purpose.
    • Snowball Sampling:
      • Special non-probability method used when the desired sample characteristic is rare.
      • Relies on referrals from initial subjects to generate additional subjects.
      • Often used in qualitative research.

    Concept Review

    • Question 1: True.
    • Question 2: True.
    • Question 3: True.
    • Question 4: D. Systematic.
    • Question 5:
      • It is not possible to get a list of all units of a population (ex.All Filipinos).
      • Cluster sampling is easier to carry out.
    • Question 6:
      • Purposive Sampling would be the best method to use because the study aims to get an understanding of the experiences of women who have undergone laser treatments and possessed narcissistic tendencies and high self-presentation.
    • Question 7:
      • Cluster sampling would be the best method to use because it is not possible to get a list of all migrant workers in East London.
    • Question 8:
      • Stratified random sampling would be the most appropriate because it would allow the researcher to select a sample of AIDS patients and Stage 4 cancer patients in a way that is representative of the population of both types of patients.
    • Question 9:
      • Stratified random sampling, to ensure that the sample is representative of the population in terms of both those who regularly watch Kdramas and follow Kpop boy bands and those who follow Western pop culture.
    • Question 10: B. Simple Sampling.
    • Question 11: C. You want to include specific subgroups in the study.
    • Question 12: A. There is a structure to the sampling frame.
    • Question 13: D. Take less time and money.
    • Question 14: C. Cluster.

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    PR II Sampling Methods PDF

    Description

    Explore the fundamental concepts of sampling, including the rationale behind sampling, confidence levels, and margin of error. Understand the importance of sample size and the implications of sampling bias on data accuracy in research. This quiz will help solidify your knowledge of effective sampling methods.

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