Sampling in quantitative research
The standard error is a statistical measure of:
The normal distribution of scores around the sample mean
The extent to which a sample mean is likely to differ from the population mean
The clustering of scores at each end of a survey scale
The degree to which a sample has been accurately stratified
The extent to which a sample mean is likely to differ from the population mean
The standard error is that which can be calculated as the difference between the population average and the sample average. Once the sample has been selected randomly, we can determine the probable difference between the sample and the population as a whole, as a range. We usually express our results, therefore, with a high degree of confidence (but not total) that our results apply to the entire population, plus or minus a little. It sounds more tentative than we might like but it cannot be more accurate than that. It should be pointed out that stratification of a sample can reduce the standard error.
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182,183
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182,183
The extent to which a sample mean is likely to differ from the population mean The standard error is that which can be calculated as the difference between the population average and the sample average. Once the sample has been selected randomly, we can determine the probable difference between the sample and the population as a whole, as a range. We usually express our results, therefore, with a high degree of confidence (but not total) that our results apply to the entire population, plus or minus a little. It sounds more tentative than we might like but it cannot be more accurate than that. It should be pointed out that stratification of a sample can reduce the standard error.
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182,183
Reference: Bryman: Social Research Methods: 5th Edition Page(s) 182,183
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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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