Research Process 4- Sampling Flashcards Preview

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Flashcards in Research Process 4- Sampling Deck (22)
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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.