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Biostatistics
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=== Sampling === Usually, a study aims to understand an effect of a phenomenon over a [[population]]. In [[biology]], a [[population]] is defined as all the [[individual]]s of a given [[species]], in a specific area at a given time. In biostatistics, this concept is extended to a variety of collections possible of study. Although, in biostatistics, a [[population]] is not only the individuals, but the total of one specific component of their [[organism]]s, as the whole [[genome]], or all the sperm [[cell (biology)|cells]], for animals, or the total leaf area, for a plant, for example. It is not possible to take the [[Measurement|measures]] from all the elements of a [[population]]. Because of that, the [[Sampling (statistics)|sampling]] process is very important for [[statistical inference]]. [[Sampling (statistics)|Sampling]] is defined as to randomly get a representative part of the entire population, to make posterior inferences about the population. So, the [[Sample (statistics)|sample]] might catch the most [[Statistical variability|variability]] across a population.<ref name=":2">{{cite journal| doi= 10.1177/0115426507022006629| pmid= 18042950| title= Biostatistics Primer: Part I| journal= Nutrition in Clinical Practice| volume= 22| issue= 6| pages= 629β35| year= 2017| last1= Overholser| first1= Brian R| last2= Sowinski| first2= Kevin M}}</ref> The [[sample size]] is determined by several things, since the scope of the research to the resources available. In [[clinical research]], the trial type, as [[inferiority]], [[Equivalence (measure theory)|equivalence]], and [[superior (hierarchy)|superior]]ity is a key in determining sample [[size]].<ref name=":3" />
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