Sampling in quantitative research
What effect does increasing the sample size have upon the sampling error?
It reduces the sampling error
It increases the sampling error
It has no effect on the sampling error
None of the above
It reduces the sampling error
Sampling theory (see fig 8.8 on p182) tells us that sampling error is measured in terms of the ‘standard error of the mean’, which means, briefly, that there will always be a high probability of having a sampling error of a particular size. By comparing the standard error in our own research (in other words, the standard deviation in our own sample from the simple average) with the generally expected standard error, we can arrive at the actual sampling error of our own research. This may sound complicated but, like question 4, our concern should be with claiming for our research findings only what can be fairly and honestly applied to the entire population. We can increase the size of our sample to reduce the sampling error but, unless we research the entire population, we can never eliminate it. This is actually good news for researchers because a sample can actually be quite small and still yield good results, “plus or minus a certain %”.
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182-184
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182-184
It reduces the sampling error Sampling theory (see fig 8.8 on p182) tells us that sampling error is measured in terms of the ‘standard error of the mean’, which means, briefly, that there will always be a high probability of having a sampling error of a particular size. By comparing the standard error in our own research (in other words, the standard deviation in our own sample from the simple average) with the generally expected standard error, we can arrive at the actual sampling error of our own research. This may sound complicated but, like question 4, our concern should be with claiming for our research findings only what can be fairly and honestly applied to the entire population. We can increase the size of our sample to reduce the sampling error but, unless we research the entire population, we can never eliminate it. This is actually good news for researchers because a sample can actually be quite small and still yield good results, “plus or minus a certain %”.
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182-184
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182-184
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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
It is helpful to use a multi-stage cluster sample when:
A. The population is widely dispersed geographically
B. You have limited time and money available for travelling
C. You want to use a probability sample in order to generalise the results
D. All of the above
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
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