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    Sampling Techniques

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    Hafsah Javed
    This document discusses different sampling techniques used in research. It describes probability sampling which uses random selection to give all population elements an equal chance of selection. Non-probability sampling does not rely on randomness. The document then outlines types of probability sampling such as simple random, systematic, stratified, and cluster sampling and provides examples. It also covers types of non-probability sampling including convenience, purposive, snowball, and quota sampling.

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    Sampling Techniques

    Uploaded by

    Hafsah Javed
    1K views11 pages
    This document discusses different sampling techniques used in research. It describes probability sampling which uses random selection to give all population elements an equal chance of selection. Non-probability sampling does not rely on randomness. The document then outlines types of probability sampling such as simple random, systematic, stratified, and cluster sampling and provides examples. It also covers types of non-probability sampling including convenience, purposive, snowball, and quota sampling.

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    This document discusses different sampling techniques used in research. It describes probability sampling which uses random selection to give all population elements an equal chance of selection. Non-probability sampling does not rely on randomness. The document then outlines types of probability sampling such as simple random, systematic, stratified, and cluster sampling and provides examples. It also covers types of non-probability sampling including convenience, purposive, snowball, and quota sampling.

    Copyright:

    © All Rights Reserved
    Download as PPTX, PDF, TXT or read online from Scribd
    Download as pptx, pdf, or txt
    1K views11 pages

    Sampling Techniques

    Uploaded by

    Hafsah Javed
    This document discusses different sampling techniques used in research. It describes probability sampling which uses random selection to give all population elements an equal chance of selection. Non-probability sampling does not rely on randomness. The document then outlines types of probability sampling such as simple random, systematic, stratified, and cluster sampling and provides examples. It also covers types of non-probability sampling including convenience, purposive, snowball, and quota sampling.

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    © All Rights Reserved
    Download as PPTX, PDF, TXT or read online from Scribd
    Download as pptx, pdf, or txt
    of 11

    Sampling Techniques

    Probability Sampling: this Sampling technique uses


    randomization to make sure that every element of the population
    gets an equal chance to be part of the selected sample. It’s
    alternatively known as random sampling.
    Non-Probability Sampling: it does not rely on randomization.
    This technique is more reliant on the researcher’s ability to select
    elements for a sample. This type of sampling is also known as
    non-random sampling.
    Types of Probability Sampling
    • Simple random sample
    • Systematic sample
    • Stratified random sample
    • Cluster sample
    Simple Random Sampling
    Every element has an equal chance of getting
    selected to be the part sample. It is used when
    we don’t have any kind of prior information
    about the target population.

    For example: Random selection of 20 students


    from class of 50 student. Each student has
    equal chance of getting selected. Here
    probability of selection is 1/50.
    Systematic Random Sampling
    Here the selection of elements is systematic and not random except
    the first element. Elements of a sample are chosen at regular intervals
    of population. All the elements are put together in a sequence first
    where each element has the equal chance of being selected.
    Stratified Random Sampling
    This technique divides the elements of
    the population into small subgroups
    (strata) based on the similarity in such
    a way that the elements within the
    group are homogeneous and
    heterogeneous among the other
    subgroups formed. And then the
    elements are randomly selected from
    each of these strata. We need to have
    prior information about the population
    to create subgroups.
    Cluster Random Sampling
    Our entire population is divided into
    clusters or sections and then the
    clusters are randomly selected. All the
    elements of the cluster are used for
    sampling. Clusters are identified using
    details such as age, gender, location etc.
    Types of Non-Probability Sampling
    • Convenience Sampling
    • Purposive Sampling
    • Snowball Sampling
    • Quota Samplings
    Convenience Sampling
    Here the samples are selected based on the availability.
    This method is used when the availability of sample is rare
    and also costly. So based on the convenience samples are
    selected.
    For example: Researchers prefer this during the initial
    stages of survey research, as it’s quick and easy to deliver
    results.
    Purposive Sampling
    This is based on the intention or the purpose of study. Only
    those elements will be selected from the population which
    suits the best for the purpose of our study.
    For Example: If we want to understand the thought
    process of the people who are interested in pursuing
    master’s degree then the selection criteria would be “Are
    you interested for Masters in..?”
    Snowball Sampling
    This technique is used in the situations where
    the population is completely unknown and rare.
    Therefore we will take the help from the first
    element which we select for the population and
    ask him to recommend other elements who will
    fit the description of the sample needed.
    Quota Sampling
    This type of sampling depends of some pre-set standard. It
    selects the representative sample from the population.

    For example: If our population has 45% females and 55%


    males then our sample should reflect the same percentage
    of males and females.

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