Statistical Sampling
Population
Def: the entire collection of things you are studying
Census: a study or survey involving the entire population
- can provide you with accurate information about your population, but it’s not always practical
Sample
a relatively small selection taken from the population that you can use to draw conclusions about the population itself.
sample survey: a study or survey involving just a sample of the population
To take a sample, start off by defining your target population, the population you want to study. Then decide on your sampling units, the sorts of things you need to sample. Once you’ve done that, draw up a sampling frame, a list of all the sampling units in your target population.
Bias
unbiased sample: representative of the target population
Biased sample: not representative of the target population
Sources of Bias
- A sampling frame where items have been left off
- An incorrect sampling unit
- Individual sampling units you chose for your sample weren’t included in your actual sample
- As an example, you might send out a questionnaire that not everybody responds to.
- Poorly designed questions in a questionnaire
- Samples that aren’t random
Sampling Methods
Simple Random Sampling
where you choose sampling units at random to form your sample. This can be with or without replacement. You can perform simple random sampling by drawing lots or using random number generators.
Stratified Sampling
where you divide the population into groups of similar units or strata. Each stratum is as different from the others as possible. Once you’ve done this, you perform simple random sampling within each stratum.
Cluster Sampling
where you divide the population into clusters where each cluster is as similar to the others as possible. You use simple random sampling to choose a selection of clusters. You then sample every unit in these clusters.
Systematic Sampling
where you choose a number,
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