Chapter 15: Sampling

Quizzes give you the chance to test your knowledge through multiple choice questions, short answers, matching activities and other revision tools.

1. Match the correct term and definition:

Terms

  • Total population
  • Sample
  • Representativeness
  • Generalizability
  • Transferability
  • Data saturation
  • Homogeneous sample
  • Heterogeneous sample
  • Probability sampling
  • Non-probability sampling
  • Simple random sampling
  • Stratified random sampling
  • Cluster sampling
  • Convenience sampling
  • Purposive sampling
  • Quota sampling
  • Snowball sampling
  • Theoretical sampling
  • Systematic sampling
  • Power calculation

Definitions

  • The study participants correspond to the wider population.
  • Participants are recruited because they have ongoing or prior experience of the phenomena the researcher is exploring.
  • The researcher pre-specifies the required characteristics of sample to ensure the final sample includes a certain number with each characteristic.
  • When data collection and analysis does not reveal any new findings and therefore recruitment of further participants is unnecessary.
  • The researcher recruits the most readily available participants who meet the study’s inclusion criteria.
  • Potential participants have an equal or random chance of being invited to take part or being allocated to groups (experimental or control group).
  • The total population is divided into sub-groups from each of which the sample is selected randomly.
  • A sample with a wide range of characteristics.
  • The researcher judges which potential participants to invite to take part in a study.
  • The entire population from which the sample is drawn.
  • The study findings can be applied to the wider population.
  • The researcher specifically recruits participants who will help them to refine or challenge the theory they are developing.
  • The most basic type of probability sampling. Each potential participant has an equal chance of being included in the sample.
  • A sample with a single or narrow range of characteristics.
  • Sampling which involves the identification of potential participants through referrals from earlier participants.
  • The study total population is divided into sub-groups which are then selected randomly.  Either the whole sub-group participates in the study or participants may be randomly selected from the sub-group.
  • Combines probability and non-probability sampling whereby a list is made of all participants in the population. The first participant is selected randomly and from then on, every nth participant is selected.
  • A method for identifying the minimum number of participants required to measure the impact of the independent variable.
  • The extent to which the findings can be applied to other similar populations in other similar settings.
  • A selection from, a sub-group or a sub-set of the total population.

Answer:

  • Total population - The entire population from which the sample is drawn.
  • Sample - A selection from, a sub-group or a sub-set of the total population. 
  • Representativeness - The study participants correspond to the wider population.
  • Generalizability - The study findings can be applied to the wider population.
  • Data saturation - When data collection and analysis does not reveal any new findings and therefore recruitment of further participants is unnecessary.
  • Transferability - The extent to which the findings can be applied to other similar populations in other similar settings.
  • Homogeneous sample - A sample with a single or narrow range of characteristics.
  • Heterogeneous sample - A sample with a wide range of characteristics.
  • Probability sampling - Potential participants have an equal or random chance of being invited to take part or being allocated to groups (experimental or control group).
  • Non-probability sampling - Participants are recruited because they have ongoing or prior experience of the phenomena the researcher is exploring.
  • Simple random sampling - The most basic type of probability sampling. Each potential participant has an equal chance of being included in the sample.
  • Stratified random sampling - The total population is divided into sub-groups from which the sample is selected randomly.
  • Cluster sampling - The study total population is divided into sub-groups which are then selected randomly.  Either the whole sub-group participates in the study or participants may be randomly selected from the sub-group.
  • Convenience sampling - The researcher recruits the most readily available participants who meet the study’s inclusion criteria.
  • Purposive sampling - The researcher judges which potential participants to invite to take part in a study.
  • Quota sampling - The researcher pre-specifies the required characteristics of sample to ensure the final sample includes a certain number with each characteristic.
  • Snowball sampling - Sampling which involves the identification of potential participants through referrals from earlier participants.
  • Theoretical sampling - The researcher specifically recruits participants who will help them to refine or challenge the theory they are developing.
  • Systematic sampling - Combines probability and non-probability sampling whereby a list is made of all participants in the population. The first participant is selected randomly and from then on, every nth participant is selected.
  • Power calculation - A method for identifying the minimum number of participants required to measure the impact of the independent variable.