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Statistical thinking for 21st century scientists

Statistical science provides a wide range of concepts and methods for studying situations subject to unexplained variability. Such considerations enter fields ranging from particle physics and astrophysics to genetics, sociology and economics, and beyond; to associated areas of application such as e...

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Detalles Bibliográficos
Autores principales: Cox, D. R., Efron, Bradley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470825/
https://www.ncbi.nlm.nih.gov/pubmed/28630933
http://dx.doi.org/10.1126/sciadv.1700768
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author Cox, D. R.
Efron, Bradley
author_facet Cox, D. R.
Efron, Bradley
author_sort Cox, D. R.
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description Statistical science provides a wide range of concepts and methods for studying situations subject to unexplained variability. Such considerations enter fields ranging from particle physics and astrophysics to genetics, sociology and economics, and beyond; to associated areas of application such as engineering, agriculture, and medicine, in particular in clinical trials. Successful application hinges on absorption of statistical thinking into the subject matter and, hence, depends strongly on the field in question and on the individual investigators. It is the job of theoretical statisticians both to be alive to the challenges of specific applications and, at the same time, to develop methods and concepts that, with good fortune, will be broadly applicable.
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spelling pubmed-54708252017-06-19 Statistical thinking for 21st century scientists Cox, D. R. Efron, Bradley Sci Adv Reviews Statistical science provides a wide range of concepts and methods for studying situations subject to unexplained variability. Such considerations enter fields ranging from particle physics and astrophysics to genetics, sociology and economics, and beyond; to associated areas of application such as engineering, agriculture, and medicine, in particular in clinical trials. Successful application hinges on absorption of statistical thinking into the subject matter and, hence, depends strongly on the field in question and on the individual investigators. It is the job of theoretical statisticians both to be alive to the challenges of specific applications and, at the same time, to develop methods and concepts that, with good fortune, will be broadly applicable. American Association for the Advancement of Science 2017-06-14 /pmc/articles/PMC5470825/ /pubmed/28630933 http://dx.doi.org/10.1126/sciadv.1700768 Text en Copyright © 2017, The Authors http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Reviews
Cox, D. R.
Efron, Bradley
Statistical thinking for 21st century scientists
title Statistical thinking for 21st century scientists
title_full Statistical thinking for 21st century scientists
title_fullStr Statistical thinking for 21st century scientists
title_full_unstemmed Statistical thinking for 21st century scientists
title_short Statistical thinking for 21st century scientists
title_sort statistical thinking for 21st century scientists
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470825/
https://www.ncbi.nlm.nih.gov/pubmed/28630933
http://dx.doi.org/10.1126/sciadv.1700768
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