Sampling Methods in Research
24 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is a key characteristic of simple random sampling?

  • It focuses solely on rare cases within the population.
  • Sampling is done non-randomly based on predetermined criteria.
  • All elements in the sampling frame have an equal chance of being selected. (correct)
  • Elements are chosen at regular intervals from a list.

    • What is a potential danger of systematic sampling?

  • It always requires a random number generator for selection.
  • It eliminates the sampling error completely.
  • It can lead to sampling bias if there is periodicity in the arrangement of elements. (correct)
  • It may be wholly representative of the population.

    • What type of sampling method ensures that appropriate numbers are drawn from homogeneous subsets of a population?

  • Simple random sampling
  • Multistage cluster sampling
  • Stratified sampling (correct)
  • Systematic sampling

    • How does disproportionate stratified sampling differ from regular stratified sampling?

    <p>It may produce samples that are not representative on some variable.</p> Signup and view all the answers

    What is the primary purpose of the National Crime Victimization Survey?

    <p>To represent the nationwide population of victims living in households.</p> Signup and view all the answers

    What does multistage cluster sampling involve?

    <p>Compiling a stratified group and then subsampling from it.</p> Signup and view all the answers

    What are primary sampling units (PSUs) in the context of the National Crime Victimization Survey?

    <p>They refer to groups of four housing units selected within census districts.</p> Signup and view all the answers

    Which type of sampling ensures that samples accurately reflect the diversity of a larger population?

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

    What is the primary purpose of standard error in the context of sampling?

    <p>To indicate how sample statistics cluster around the population parameter</p> Signup and view all the answers

    When discussing confidence levels and intervals, what is essential for accurate sampling statements?

    <p>Stating a confidence level and a confidence interval</p> Signup and view all the answers

    In the context of probability sampling, what does the sampling frame represent?

    <p>A quasi-list from which a probability sample is derived</p> Signup and view all the answers

    How is the accuracy of sample statistics usually expressed?

    <p>As a level of confidence within a specified interval</p> Signup and view all the answers

    What might be a reasonable response to someone claiming 100% confidence in their survey results?

    <p>All surveys have inherent errors that cannot allow for absolute certainty</p> Signup and view all the answers

    Which sampling design would inherently minimize sampling bias?

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

    What is a necessary condition for making valid inferences from a sample to a larger population?

    <p>Samples must be randomly selected from a well-defined sampling frame</p> Signup and view all the answers

    Which of the following is NOT a key feature of probability sampling designs?

    <p>Deliberate selection of specific individuals</p> Signup and view all the answers

    What is the chief criterion of a sample’s quality?

    <p>The degree to which it is representative of the population</p> Signup and view all the answers

    Which of the following accurately describes probability sampling?

    <p>Each member has a known, nonzero probability of being selected</p> Signup and view all the answers

    Which sampling method is considered the most fundamental technique in probability sampling?

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

    What is a notable feature of the National Crime Victimization Survey?

    <p>It uses multistage cluster sampling techniques</p> Signup and view all the answers

    Which of the following describes nonprobability sampling methods?

    <p>They do not allow for every member of the population to have a chance of selection</p> Signup and view all the answers

    Which method is an example of nonprobability sampling?

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

    What does stratified sampling allow researchers to do?

    <p>To ensure all subgroups are represented according to their proportion in the population</p> Signup and view all the answers

    What is the main limitation of nonprobability sampling methods?

    <p>They are less likely to yield reliable results</p> Signup and view all the answers

    Study Notes

    Sampling Methods

    • Sampling is the process of selecting observations.
    • It's often not possible or necessary to collect information from everyone.
    • Researchers select a smaller subset of observations and generalize the findings to the entire population.

    Learning Objectives

    • Understanding probability sampling allows representation of large populations with smaller subsets.
    • The quality of a sample is determined by how well it represents the population.
    • Probability sampling ensures every member of the population has a known, non-zero chance of selection.
    • Probability sampling methods lead to representative samples.
    • Sample statistics, grounded in sampling distributions and probability theory, allow estimating population parameters.
    • Simple random sampling is the foundational probability sampling technique.
    • Different probability sampling designs (systematic, stratified, multistage cluster) can be used.
    • The National Crime Victimization Survey (NCVS) and the British Crime Survey employ multistage cluster sampling.
    • Probability sampling is statistically more representative than non-probability sampling.

    Introduction

    • Sampling involves selecting a smaller group from a larger population.
    • Collecting data from everyone isn't always possible or practical.
    • Sampling helps researchers generalize findings from a subset to the wider population.

    The Logic of Probability Sampling

    • Probability sampling enables researchers to generalize findings about a select group to a larger unobserved population.
    • Each member in the population has a known and equal chance of inclusion in the sample.
    • Samples must reflect the variations within the population to be representative.

    Conscious and Unconscious Sampling Bias

    • Researchers should be aware of potential bias.
    • A biased sample does not fully represent the larger population.
    • Equal Probability of Selection Method (EPSEM) ensures representative samples.
    • Samples with characteristics similar to the population are representative.

    Sampling Distribution

    • Sample element: individual or unit of study.

    • Population: entire group of interest.

    • Population parameter: value of a variable for the population.

    • Sample statistic: summary description of a variable in the sample.

    • Sample statistics are used to estimate population parameters.

    • Purpose of sampling: selecting elements in a way to accurately portray population parameters.

    • Random selection is crucial.

    • Sampling distribution: range of sample statistics obtained from many samples.

    • Sampling frame: list of all elements in the population used for random selection.

    • Increasing the number of samples and interviewees increases the range of possible estimates from sampling.

    Estimating Sampling Error

    • Random samples from populations generate sample statistics dispersed around the population parameter.

    • Probability theory provides formulas for estimating the closeness of sample specifics to a population parameter.

    • Standard error measures sampling error.

    • It indicates how the sample statistics distribute around the population parameter.

    Confidence Levels and Intervals

    • Sampling error accuracy is expressed using confidence intervals.
    • Confidence intervals indicate a specified interval where population parameters likely lie.
    • Confidence levels help determine the appropriate sample size for a study.

    Discussion Questions

    • What is a 100% confidence level response for survey results?
    • What is the decision if choosing between NCVS or the British Crime Survey?
    • What are the strengths and weaknesses of snowball sampling for research?

    Nonprobability Sampling

    • Nonprobability sampling methods might be used when impossible to collect a probability sample.
    • Probability that an element is included in the sample is not known.
    • Cannot generalize to larger populations (e.g, purposive, quota, snowball).

    Nonprobability Sampling, cont.

    • Purposive sampling: selecting samples based on the researcher's judgment and study purpose.
    • Quota sampling: creating a sample reflecting population characteristics.
    • Snowball sampling: identifying participants through referrals from initial participants.

    Multistage Cluster Sampling

    • Multistage cluster sampling involves selecting from stratified clusters.
    • May be used when creating an exhaustive list of the population is impossible.

    National Crime Victimization Survey

    • This survey aims to represent the U.S. population aged 12 and older living in households.
    • Primary sampling units (PSU) are automatically included, based on size and other characteristics.
    • Census enumeration districts (CED) are selected, and clusters of four housing units are selected.

    British Crime Survey

    • The survey uses 289 parliamentary constituencies.
    • The selection is stratified, considering geographic area and population density.
    • Two sample points are selected and further divided into four segments for different addresses.
    • One segment is randomly selected, and disproportionate sampling is used for inner-city residents.
    • Eligible individuals are identified and selected by interviewers.

    Populations & Sampling Frames

    • Various probability sampling designs can be used in different research purposes.
    • Key aspect: relationship between population and sampling frame.
    • Sampling frame: quasi-list of elements from which a probability sample is drawn.

    Simple Random Sampling

    • Sampling frame elements are numbered, and random numbers determine sample inclusion.
    • Forms the basis for probability theory and estimating population parameters.

    Systematic Sampling

    • Elements in a list are systematically selected for inclusion in the sample.
    • A random start is crucial to avoid bias.
    • Periodicity in the list can create bias.

    Stratified Sampling

    • Stratified sampling ensures appropriate numbers from homogeneous subsets within a population.
    • Method creates more representative samples.
    • Disproportionate stratified sampling allows capturing rare cases more effectively.

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    Related Documents

    Maxfield 8e PPT Ch08 Sampling PDF

    Description

    This quiz explores various sampling methods used in research, focusing on probability sampling techniques. Understand how to select representative samples from larger populations and the importance of sample statistics in estimating population parameters. Test your knowledge on different sampling designs and their applications.

    More Like This

    Use Quizgecko on...
    Browser
    Open
    Browser
    Browser