Karteikarten
Sampling
Karten in diesem Stapel (8)
- 1Target Populations and Sampling MethodsTarget population: the wider group of people that research findings should apply to.
Biased sample: a sample that is not representative of the target population. - 2Representative sample: a cross-section that is typical of the target population. Sampling frame: a section of the target population from which the sample is literally drawn.Researchers aim to get a sample that is representative of the target population that they are interested in.
- 3Opportunity Sampling Participants are chosen because they are convenient. This means that they might have been selected because they have volunteered, because they are in the locality, or because they are known to the researcher. The researcher uses participants that s/he has the opportunity to use.Strengths
Less time-consuming than other techniques because time is not spent planning and using sophisticated systems for selection. - 4Weaknesses Likely to be a biased sample If people come from the same locality they may be similar in terms of their characteristics (e.g. all University students) The researcher may show bias when choosing the participants whether intentional or not (e.g. know they will behave in a certain way)Systematic Sampling
Participants are chosen mathematically, choosing every nth person. For example, from a sampling frame of 100 people from which she wanted to select 20 participants, every 5th person would be chosen from a list or register. - 5Strengths It avoids bias as, once the researcher has decided what number they are gong to use for the selection, they have no control over who is being selected. The law of probability says that the researcher will normally get a representative sample.Weaknesses
There is a small chance of a ‘freak’ sample which would not be representative.
It is not completely objective because the researcher may decide on how people are listed before the selection and on what number to use for the system. - 6Stratified Sampling Participants are chosen after the sampling frame has been stratified (grouped). A certain number of people are randomly chosen from each group in the proportions that they appear in the target population.Strengths
Creates a representative sample, making sure that all key characteristics are represented.
It is relatively objective because once the sampling frame is stratified it is normally left to chance who is selected from each strata. - 7Weaknesses It is time-consuming because all potential participants need to be assessed and categorised before a sample can be drawn. The researcher may not identify all the key characteristics for stratification meaning that the sample is not representativeRandom Sampling
Participants are chosen mathematically, using chance. Every member of the sampling frame has an equal chance of being selected. E.g. selected by computer from the electoral roll. - 8Strengths It avoids bias as the researcher has no control over who is selected. The law of probability says that the researcher will normally get a representative sample.Weaknesses
It is time-consuming because all potential participants need to be identified before a sample can be drawn.
There is a small chance that a bias sample may be drawn, which would be unrepresentative.
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- A Levels Psychology (research methods) Karteikarten am Sampling, erstellt von 08shunt.gemma am 22/01/2015.
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