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A sample size of one is sufficient to enable you to calculate a statistic.
The sample size required for a "good" statistical estimate will depend on the variability of the characteristic being studied as well as the accuracy required in the result. A rare characteristic will require a large sample. A high degree of accuracy will also require a large sample.
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How does the sample size affect an experiment?
Sample size greatly reduces any error to randomness in a given sample. Each experiment requires a proper size of a sample. The better it is fitted to the experiment, the better is the result. For example, if you are trying to find out the study habits of students at your school of 1000 kids, a sample size of 50 would be sufficient. However, if you are trying to find out the study habits of students across the US, a sample size of at least several hundred-thousand would be required, preferably several million.
Factors to consider in determining sample size?
Factors that determine sample size
What is a sample size?
When something is a sample size, that means it is smaller than the size that is normally available for purchase. Sample size products are usually enough to let you try something before you buy it.
How does sample size affect the margin of error?
The larger the sample size, the smaller the margin of error.
Why would having a larger sample size be a better idea than having a samll sample size when doing an experiment?
less bias and error occur when sample size is larger
