Sample size
Sample size
Sample size (pronunciation: /ˈsæmpl ˈsaɪz/) is a term used in statistics and research design to refer to the number of observations or replicates used in a statistical sample. The size of a sample influences the accuracy of the estimates and hypothesis tests that can be made from the sample data.
Etymology
The term "sample size" originates from the field of statistics. The word "sample" comes from the Old French esample, meaning "a model or example to be followed", while "size" comes from the Old Norse síza, meaning "to measure". Together, they refer to the measure of a subset or example taken from a larger population for the purpose of statistical analysis.
Related terms
- Population: The entire set of individuals or objects of interest or the measurements obtained from all individuals or objects of interest.
- Sampling error: The error caused by observing a sample instead of the whole population.
- Power (statistics): The probability that a statistical test will reject a false null hypothesis.
- Effect size: A quantitative measure of the magnitude of a phenomenon.
- Confidence interval: An estimated range of values which is likely to include an unknown population parameter.
See also
External links
- Medical encyclopedia article on Sample size
- Wikipedia's article - Sample size
This WikiMD article is a stub. You can help make it a full article.
Languages: - East Asian
中文,
日本,
한국어,
South Asian
हिन्दी,
Urdu,
বাংলা,
తెలుగు,
தமிழ்,
ಕನ್ನಡ,
Southeast Asian
Indonesian,
Vietnamese,
Thai,
မြန်မာဘာသာ,
European
español,
Deutsch,
français,
русский,
português do Brasil,
Italian,
polski