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Statistical Surveys 2. Sampling Methods. Sampling techniques. A random sample is a sample drawn in such a way that each element of the population has a chance of being selected. A random sample is likely to be representative of the population. Simple Random Sample.
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Statistical Surveys 2 Sampling Methods
Sampling techniques • A random sample is a sample drawn in such a way that each element of the population has a chance of being selected. • A random sample is likely to be representative of the population.
Simple Random Sample A simple random sample is a sample that is selected in such a way that each member has the same chance of being included in the sample. This method is best suited to a reasonably small sample frame. It becomes tedious time-consuming if the population is large.
Systematic Random Sample • Starting at a random point, and sampling every nth individual (such as every 15th person on the school roll). • This method is more convenient for a large population than the simple random sample. • This method is likely to give a sample which is representative of the population
Stratified Random Sample • In a stratified random sample we first divide the population into groups which are called strata. Then a sample is selected from each strata in proportion to the size of the group. The collection of all samples from all strata gives the stratified random sample.
Quota sample • A quota sample is like a stratified sample, except that the sample may or may not be chosen in a random way. • In a quota sample, a researcher keeps sampling until they have enough of each category being investigated. • Eg all age groups in the NZ health survey
Cluster Sample • In cluster sampling the whole population is first divided into geographical groups called clusters. Each cluster is representative of the population. Then a random sample of clusters is selected. Finally a random sample is taken from each of the selected clusters.
Convenience sampling • The sample is taken from the easiest part of the population to reach. • That sample may or may not be representative of the population.
Self-selected sampling • The sample is open to anyone and people can decide whether to be part of it. • It is very likely that a self-selected sample will be biased.