Sampling

• Types of sample: Random samples and Non-random samples
• Random sampling: A sampling technique that involves selecting a sample from a population by using a random method, uses a sampling frame. E.G. stratified, systematic, simple-random.
• Non-random sampling: Sampling procedure that does not follow a random sampling procedure, doesn't need a sampling frame. E.G. quota, snowball, volunteer, opportunity.
• Pilot study: A small-scale study that is carried out before a larger study to test the feasibility of the research design. It helps to operationalize key concepts, train staff, test questions, figure out timing and check validity/reliability.
• Snowball sampling: Collecting a sample by using key individuals who are asked to suggest others who may take part adding to the snowball with more people. E.G. trying to find criminals.

  Evaluation- Not always representative, can introduce bias
• Quota sampling: The population is first stratified then each interviewer is given a quota to fill, the interviewer keeps at the task until the quota is full. E.G when ages need to be split up.

  Evaluation: is proportional to population, could introduce bias
• Random sampling: Names may be drawn from a hat so everyone has an equal chance of being selected. A sampling frame is needed. E.G. a survey.

  Evaluation: No bias, not representative
• Systematic sampling: Every Nth person in the sampling frame is selected, could be every third person. The first person is chosen choosing simple-random methods. E.G. for a quick sample.

  Evaluation: requires sampling frame, no bias.
• Stratified sampling: The researcher stratifies the population in the sampling frame, then simple random sampling is used to find enough people for each stratum. E.G. for guaranteed representation of minority groups.

  Evaluation: Requires sampling frame, No bias