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→Application
== Application ==
== Application ==
[[File:Assessing the role of a confounder.png|thumb|219x219px|Confounding factors are important to consider in clinical trials]]
[[File:Confounding_factors_are_important_to_consider_in_clinical_trials.png|thumb|219x219px|Confounding factors are important to consider in clinical trials]]
Stratified random sampling is useful and productive in situations requiring different [[weighting]]s on specific strata. In this way, the researchers can manipulate the selection mechanisms from each strata to amplify or minimize the desired characteristics in the survey result.<ref>{{Cite web|url=https://www.thoughtco.com/stratified-sampling-3026731|title=Understanding Stratified Samples and How to Make Them|last=Crossman|first=Ashley|date=Jan 27, 2020|website=ThoughtCo|language=en|access-date=2020-04-07}}</ref>
Stratified random sampling is useful and productive in situations requiring different [[weighting]]s on specific strata. In this way, the researchers can manipulate the selection mechanisms from each strata to amplify or minimize the desired characteristics in the survey result.<ref>{{Cite web|url=https://www.thoughtco.com/stratified-sampling-3026731|title=Understanding Stratified Samples and How to Make Them|last=Crossman|first=Ashley|date=Jan 27, 2020|website=ThoughtCo|language=en|access-date=2020-04-07}}</ref>
In real life, stratified random sampling can be applied to results of election polling, investigations into income disparities among social groups, or measurements of education opportunities across nations.<ref name=":3" />
In real life, stratified random sampling can be applied to results of election polling, investigations into income disparities among social groups, or measurements of education opportunities across nations.<ref name=":3" />
== Stratified randomization in clinical trials ==
== Stratified randomization in clinical trials ==