Sampling Techniques

    OCR
    GCSE

    Sampling constitutes the foundational mechanism of research design, determining the extent to which findings can be generalised from a subset to a target population. Candidates must understand the dichotomy between probability (random) and non-probability (non-random) techniques, linking these choices to the theoretical schism between Positivism (seeking representativeness and patterns) and Interpretivism (seeking validity and depth). Mastery requires evaluating how practical constraints (access, cost) and the nature of the sampling frame influence the selection of technique.

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    Objectives
    4
    Exam Tips
    4
    Pitfalls
    3
    Key Terms
    4
    Mark Points

    What You Need to Demonstrate

    Key skills and knowledge for this topic

    • Award marks for precise definitions of sampling types (e.g., defining 'Random' as every member of the target population having an equal chance of selection).
    • Credit responses that explicitly link the choice of sampling method to the specific context or target population provided in the source material.
    • Candidates must evaluate the method's ability to achieve representativeness and generalisability.
    • Award marks for identifying practical issues such as access to a sampling frame or time/cost constraints associated with specific techniques like Stratified sampling.

    Marking Points

    Key points examiners look for in your answers

    • Award marks for precise definitions of sampling types (e.g., defining 'Random' as every member of the target population having an equal chance of selection).
    • Credit responses that explicitly link the choice of sampling method to the specific context or target population provided in the source material.
    • Candidates must evaluate the method's ability to achieve representativeness and generalisability.
    • Award marks for identifying practical issues such as access to a sampling frame or time/cost constraints associated with specific techniques like Stratified sampling.

    Examiner Tips

    Expert advice for maximising your marks

    • 💡When asked to justify a sampling method, always contrast it with a rejected alternative to strengthen the argument.
    • 💡Use the term 'Generalisability' only when the sample is proven to be representative of the wider population.
    • 💡Check if the question provides a 'sampling frame' (list of names); if not, probability methods like Random or Systematic are impossible.
    • 💡For 12-mark 'Discuss' questions, ensure you evaluate the sampling method's impact on the validity of the final data.

    Common Mistakes

    Pitfalls to avoid in your exam answers

    • Defining 'Random sampling' colloquially as 'picking anyone' rather than 'equal chance of selection'.
    • Confusing 'Systematic sampling' (every nth person) with 'Stratified sampling' (proportional representation of subgroups).
    • Stating a method is 'quick and easy' without explaining why (e.g., failing to specify that Opportunity sampling requires no sampling frame).
    • Failing to link the critique of the sample to the specific research aim (e.g., criticizing a small sample size without referencing the specific population being studied).

    Key Terminology

    Essential terms to know

    Likely Command Words

    How questions on this topic are typically asked

    Identify
    Describe
    Explain
    Discuss
    Evaluate
    Compare

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