What Are the Advantages of Good Sample Size?

Written by stuart robertson
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What Are the Advantages of Good Sample Size?
In petri dish experiments, additional samples can often be grown, which makes it easy to obtain a good sample size. (Jupiterimages/Photos.com/Getty Images)

No matter what kind of research you are conducting, a good sample size is a necessity, and a large sample size is almost always better than a small sample size. Not only are there many advantages to having a large sample size, but for many studies there is a minimum sample size; less than that and the results are meaningless.

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Minimum Sample Size

A sample is a representation of a larger population. For the sample to be a good sample, it must be of sufficient size to reflect the full diversity of that population. If you were taking a sample of rocks on a beach, say, to determine the most common kind of rock found there, but collected only 10 rocks, in all likelihood your sample would not reflect the true distribution of rock types on the beach.

More Data Is Always Better

A good sample size can be of a minimum size, but the best sample size is almost always the largest sample size possible. A larger sample size will give a more accurate representation of the entire population. The most accurate way to determine the various kinds of rocks present on a section of beach would be to account for every single rock there. The most accurate sample, then, would not be a sample at all, but rather the entire beach.

Better Chance of Outliers

Another reason that a good sample size is usually a large sample size is the greater chance to find outliers among the population. Depending on the objective of the research, outliers may not be a good thing, but if what you are looking for is outliers, a large sample size is a must. If you were looking to see how many samples of a rare kind of rock you could find on a beach, a larger sample size would give you more accurate results.

Results More Credible

Studies and surveys with a good sample size are also usually taken more seriously than those that meet only minimum requirements for sample size. A larger sample size better lends itself to accurate statistical analysis, and the results are thus more meaningful. Other researchers and people who read research are more likely to take the results of research seriously if the sample size is sufficient. A too-small sample size is one common criticism of many studies.

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