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Planning and Conducting Research

Self-selected, snowball and stratified sampling

  • 3 things to know
  • Component 01

Overview

Recall questions on self-selected, snowball and stratified sampling with their strengths and weaknesses, volunteer bias, calculating a stratified sample, why a large sample can still be unrepresentative, and identifying the technique in a study.

What you need to know

Answer each one before you reveal it.

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Evaluation

When is snowball sampling particularly useful?

Key term

Explain why a very large sample can still be unrepresentative.

Key term

Describe self-selected sampling.

Questions from this subtopic

Each one with the model answer underneath.

  1. 1

    Describe self-selected sampling.

    Model answer

    Participants put themselves forward in response to an advertisement or an open request for volunteers.

  2. 2

    Give one strength of self-selected sampling.

    Model answer

    Volunteers are willing and committed, so they are less likely to drop out and recruitment costs the researcher little effort.

  3. 3

    What is volunteer bias?

    Model answer

    The tendency for people who come forward to share particular characteristics, such as being more helpful or more curious, which makes the sample unrepresentative.

  4. 4

    Describe snowball sampling.

    Model answer

    One participant who fits the criteria is recruited and then asked to identify others, who in turn recruit further participants.

  5. 5

    When is snowball sampling particularly useful?

    Model answer

    When the target population is small, hidden or hard to reach, so that no list of its members exists.

  6. 6

    Give one weakness of snowball sampling.

    Model answer

    Because participants recruit people they already know, the sample tends to come from one narrow social network and is unlikely to be representative.

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