Quiz

Take the quiz to test your understanding of the key concepts covered in the chapter. Try testing yourself before you read the chapter to see where your strengths and weaknesses are, then test yourself again once you’ve read the chapter to see how well you’ve understood.

Match the correct term and definition:

• Total population
• Sample
• Representativeness
• Generalisability
• 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

• 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 a sample to ensure the final sample includes a certain number with each characteristic.
• When data collection and analysis do not reveal any new findings recruitment of further participants is therefore 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.

• 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 do 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.