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Venn diagrams and probability in clinical research

Bulanov, NМ; Blyuss, OB; Munblit, DB; Nazarenko, TV; Butnaru, DV; Nadinskaia, MY; Zaikin, AA; (2020) Venn diagrams and probability in clinical research. Sechenov Medical Journal , 11 (4) pp. 5-14. 10.47093/2218-7332.2020.11.4.5-14. Green open access

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Abstract

Statistics is the science dealing with the collecting, summarizing and interpreting of associations in research data, and has a leading role in medical research. This article is an introductory publication in a series devoted to biomedical statistics. The aim of this article is to acquaint the readers with the basic concepts of Venn diagrams, probability and set theory, which are required to further understand descriptive and inferential statistics. First, we discuss the applications of Venn diagrams in current clinical research. Then we discuss the definitions of sample space, events, basic set operations (union and intersection) and their implementation in the classical approach to probability theory. All examples are introduced with Venn diagrams to illustrate the cases.

Type: Article
Title: Venn diagrams and probability in clinical research
Open access status: An open access version is available from UCL Discovery
DOI: 10.47093/2218-7332.2020.11.4.5-14
Publisher version: https://doi.org/10.47093/2218-7332.2020.11.4.5-14
Language: English
Additional information: This work is licensed under a CC BY License.
Keywords: Statistics, set theory, probability, Venn diagram
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Womens Cancer
URI: https://discovery.ucl.ac.uk/id/eprint/10127217
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