Sampling in quantitative research
It is helpful to use a multi-stage cluster sample when:
The population is widely dispersed geographically
You have limited time and money available for travelling
You want to use a probability sample in order to generalise the results
All of the above
All of the above
The primary reason for using a multi-stage cluster sample is geographic dispersion of the population. This automatically involves considerably extra time and money spent on travelling to conduct the interviews or surveys. However, if you select a sample on a more local basis you will not be able to extrapolate your results to the entire population. The solution is to select regions at random, for example, in the first stage, followed by cities, perhaps, as a second stage and local council areas as a third stage. In other words, by using this ‘multi-stage’ approach, we select ‘clusters’ of the national population at random, which can produce samples more easily studied.
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 179, 180
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 179, 180
All of the above The primary reason for using a multi-stage cluster sample is geographic dispersion of the population. This automatically involves considerably extra time and money spent on travelling to conduct the interviews or surveys. However, if you select a sample on a more local basis you will not be able to extrapolate your results to the entire population. The solution is to select regions at random, for example, in the first stage, followed by cities, perhaps, as a second stage and local council areas as a third stage. In other words, by using this ‘multi-stage’ approach, we select ‘clusters’ of the national population at random, which can produce samples more easily studied.
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 179, 180
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 179, 180
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The findings from a study of young single mothers at a university can be generalised to the population of:A. All young single mothers at that university
B. All young single mothers in that society
C. All single mothers in all universities
D. All young women in that university
A simple random sample is one in which:
A. From a random starting point, every nth unit from the sampling frame is selected
B. A non-probability strategy is used, making the results difficult to generalize
C. The researcher has a certain quota of respondents to fill for various social groups
D. Every unit of the population has an equal chance of being selected
Which of the following is not a characteristic of quota sampling?
A. The researcher chooses who to approach and so might bias the sample
B. Those who are available to be surveyed in public places are unlikely to constitute a representative sample
C. The random selection of units makes it possible to calculate the standard error
D. It is a relatively fast and cheap way of finding out about public opinions
Snowball sampling can help the researcher to:
A. Access deviant or hidden populations
B. Theorise inductively in a qualitative study
C. Overcome the problem of not having an accessible sampling frame
D. All of the above
Which of the following is not a type of non-probability sampling?
A. Snowball sampling
B. Stratified random sampling
C. Quota sampling
D. Convenience sampling
A sampling frame is:
A. A summary of the various stages involved in designing a survey
B. An outline view of all the main clusters of units in a sample
C. A list of all the units in the population from which a sample will be selected
D. A wooden frame used to display tables of random numbers
What effect does increasing the sample size have upon the sampling error?
A. It reduces the sampling error
B. It increases the sampling error
C. It has no effect on the sampling error
D. None of the above
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