Research Process 4- Sampling Flashcards
1
Q
What is the total population ?
A
- Referred to as the study’s population, target or wider population.
- Have at least one population or characteristic in common in order to make them suitable for the study
- Identify the size of the population
2
Q
What is a sample ?
A
- A sub-group of the total population
- Participants that actually take part in the study
3
Q
What is representativeness ?
A
- Commonly associated with quantitative research.
- The intention is to ensure that the participants who take part in the study have the same characteristics as those in the study’s population.
- The sample is as close as possible to represent the total population
- Allows the researcher to generalise the study findings
- In qualitative research the word normally used is reflect.
4
Q
What is generalisability ?
A
- Closely associated with quantitative research
- When the study findings are generalised or applied to the study’s population
- In order to generalise the sample must be a representative of the population
- Generalisability requires representativeness
5
Q
What is transferability ?
A
- Qualitative research associated
- Not possible to generalise qualitative data
6
Q
What is data saturation
A
- Association with qualitative research and grounded theory
- New data or information is discovered both in terms of the depth and breadth of the data.
- The point at which saturation is reached can usually be pinpointed in retrospect, it is often used to determine the size of a sample.
7
Q
What is homo/heterogenous sample ?
A
- Homo- single or narrow range of characteristics
- Hetro- wide range of characteristics.
8
Q
What are the sampling strategies ?
A
- The researcher first needs to decide if it is feasible to involve the total population or if a sample of the population is required.
- It may be unethical and resoursely restricted to involve the whole population in a study if the findings can be confirmed by involving just a sample of a population.
- Two broad sampling strategies:
o Probability sampling- quantitative
o Non-probability sampling-qualitative
o Also systematic sampling a strategy uses both probability and non-probability approaches.
9
Q
What is probability sampling ?
A
- Selection of a proportion of the population using random procedures
- Random sampling: everyone in the study’s total population has an equal chance to being included.
- This way the sample is representative of the population and so generalisable.
10
Q
What are the three common probability sampling ?
A
- Simple random sampling
- Stratified random sampling
- Cluster sampling
11
Q
What is simple random sampling ?
A
- each potential participant has an equal chance of being included in the sample
- usually selection of the sample done by computer program or a random table.
12
Q
What is stratified random sampling ?
A
- The population is divided into sub-groups from which the sample is selected randomly.
- Using this strategy can be more representative of the total population
13
Q
What is cluster sampling ?
A
- When the study population is divided into sub-groups and the clusters are then selected randomly
- Either the whole cluster participated in the study or participants may be randomly selected from the cluster.
14
Q
What is non-probability sampling ?
A
- Non-random procedures
- No intention to generalise the findings to the study population
- Sample size is usually determined by data saturation
- Perceived to be biased
15
Q
What are the common non-probability sampling strategies ?
A
- Convenience sampling
- Purposive sampling
- Quota sampling
- Snowball sampling
- Theoretical sampling
16
Q
What is convenience sampling ?
A
- Researcher recruits the most readily available participants who meets the study’s inclusion criteria.
- A risk that the sample will not reflect the characteristics of the population.
17
Q
What is purposive sampling ?
A
- Usually used in the early stages of the grounded theory or phenomenological strategy
- Participants who meet the study’s inclusion are recruited
- The researcher should constantly monitor the configurations of the sample and should attempt to recruit individuals to address any shortfalls of the sample
- Can be difficult if the research was very specific
18
Q
What is quota sampling ?
A
- The researcher pre-specifies the required characteristics of the sample to ensure the final sample includes a certain number with each characteristics
19
Q
What is snowball sampling ?
A
- Involves the identification of potential participants through referrals from earlier participants
- Useful way of accessing difficult to reach participants.
20
Q
What is theoretical sampling ?
A
- Researchers using concepts and ideas rather than participants.
- Enables the researcher to collect data from a range of sources
21
Q
What is systematic sampling ?
A
- Sometimes referred to as list sampling
- Strategy starts with the generation of a list of all participants in the population.
- The selection of the first participant is undertaken randomly and from then on, every nth participant is selected for the study.
- Therefore the inclusion of a participant is determined by their position of the list.
22
Q
What are the important questions ?
A
- Important question: who should take part in the study and who should not determined by the study’s aims and objectives.
- How many participants do I need?
- The sample size need to be large enough to achieve the research aims but a sample that is too large in unethical and costly.
- In quantitative research the sample size is known before the study starts, whilst qualitative research, the sample size is known once the study evolves.
- Quantitative research: the larger the group the more accurate the findings are and therefore generalisable. Should be determined by a power calculation. Done by the statistical team. The calculation is based on outcome measures and measurement tools (etc).
- Qualitative data is usually determined by data saturation: therefore can only indicate the likely number of participants at the beginning. Determining the point at which data has saturated can be hard.
