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types of sampling (cluster sample (Units in the population can often be…
types of sampling
cluster sample
Units in the population can often be found in certain geographic groups or "clusters" for example, primary school children in Derbyshire.
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Quota sampling
The aim is to obtain a sample that is "representative" of the overall population.
The population is divided ("stratified") by the most important variables such as income, age and location. The required quota sample is then drawn from each stratum.
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disad: not random, biased;
Need to understand the population to be able to identify the basis of stratification
Simply random sampling
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ad: easily designed and interpreted;
can calculate both the estimate of population and sampling error
disad: need a complete and accurate populating listing;
May not be practical if the sample requires lots of small visits over the country
Systematic sampling
After randomly selecting a starting point from the population between 1 and n, every nth unit is selected.
n equals the population size divided by the sample size.
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sample design
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affects the size of the sample + the way of analysis;
the more complex the design, larger the sample size will be.
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Sample Size
For any sample design, deciding upon the appropriate sample size will depend on several key factors:
No estimate taken from a sample is expected to be exact: assumptions about the overall population based on the results of a sample will have an attached margin of error
To lower the margin of error usually requires a larger sample size: the amount of variability in the population, ie the range of values or opinions, will also affect accuracy and therefore size of the sample
The confidence level is the likelihood that the results obtained from the sample lie within a required precision: the higher the confidence level, the more certain you wish to be that the results are not atypical. Statisticians often use a 95% confidence level to provide strong conclusions
Population size does not normally affect sample size: in fact the larger the population size, the lower the proportion of that population needs to be sampled to be representative. It's only when the proposed sample size is more than 5% of the population that the population size becomes part of the formulae to calculate the sample size
population
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units in the population can be identified by existing information
such as pay-rolls, company lists, government registers etc.
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For example, postcodes have become a well-used means of selecting a sample.