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Sampling and data collection
It is rarely possible to ask everyone. A good sample represents the whole population fairly.
Population and sample
The population is everyone or everything being studied. A sample is part of it.
Samples are quicker and cheaper, but must be representative.
Samples are quicker and cheaper, but must be representative.
Random sampling and bias
In a random sample, every member has an equal chance of being chosen, for example using a random number generator.
A sample is biased if some groups are more likely to be chosen, such as asking only people at a gym about exercise.
A sample is biased if some groups are more likely to be chosen, such as asking only people at a gym about exercise.
Capture-recapture (Higher)
Catch and mark M animals. Later catch n, of which m are marked.
Estimate population N = M × nm
Estimate population N = M × nm
50 fish are tagged. Later 40 are caught and 8 are tagged. Estimate the population.
- N = 50 × 408
Answer: 250
A sample should be random and representative to avoid bias. Bigger samples are more reliable. Capture-recapture: N = (M × n) ÷ m.
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