In research, the sample should <u>represent</u> the population from which it is drawn as much as possible.
<h3>What of the population should be the sample?</h3>
Sampling individuals from a population into a sample is a critically important step in any biostatistical analysis, because we are making generalizations about the population based on that sample. When selecting a sample from a population, it is important that the sample is representative of the population, i.e., the sample should be similar to the population with respect to key characteristics.
When selecting a sample, we need to know how many people to study and which people from the population to select. A study's sample size depends on many factors, and will be the topic of future study. Presently, let us consider how to select a valid sample.
A valid sample is one that represents the population to which inferences will be made. And although there is no fail-safe way to ensure sample representativeness, much has been learned over the past half century about sampling to maximize a sample's usefulness.
One thing that has been learned is that, whenever possible, a probability sample should be used.
A probability sample is a sample in which:
- Every population member has a known probability of being included in the sample,
- The sample is drawn by some method of random selection consistent with these probabilities, and
- These probabilities are considered when making estimates from the sample
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