DEFINITION of 'Simple Random Sample'
A subset of a statistical population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group. An example of a simple random sample would be a group of 25 employees chosen out of a hat from a company of 250 employees. In this case, the population is all 250 employees, and the sample is random because each employee has an equal chance of being chosen.
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BREAKING DOWN 'Simple Random Sample'
A sampling error can occur with a simple random sample if the sample doesn't end up accurately reflecting the population it is supposed to represent. For example, in our simple random sample of 25 employees, it would be possible to draw 25 men even if the population consisted of 125 women and 125 men. For this reason, simple random sampling is more commonly used when the researcher knows little about the population. If the researcher knew more, it would be better to use a different sampling technique, such as stratified random sampling, which helps to account for the differences within the population (such as age, race or gender).

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When is it better to use systematic over simple random sampling?
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What is the criteria for a simple random sample?
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What are the best selection methods for creating a simple random sample?
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What are the advantages of using a simple random sample to study a larger population?
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What's the difference between a representative sample and an unbiased sample?
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Simple random sampling statistically measures a subset of individuals selected from a larger group or population to approximate ... Read Full Answer >> 
What is the difference between a simple random sample and a stratified random sample?
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What are the advantages and disadvantages of stratified random sampling?
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What are some examples of stratified random sampling?
Simple random sampling is a sample of individuals that exist in a population; the individuals are randomly selected from ... Read Full Answer >>