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Empowering statistical methods for cellular and molecular biologists

We provide guidelines for using statistical methods to analyze the types of experiments reported in cellular and molecular biology journals such as Molecular Biology of the Cell. Our aim is to help experimentalists use these methods skillfully, avoid mistakes, and extract the maximum amount of infor...

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Detalles Bibliográficos
Autores principales: Pollard, Daniel A., Pollard, Thomas D., Pollard, Katherine S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724699/
https://www.ncbi.nlm.nih.gov/pubmed/31145670
http://dx.doi.org/10.1091/mbc.E15-02-0076
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author Pollard, Daniel A.
Pollard, Thomas D.
Pollard, Katherine S.
author_facet Pollard, Daniel A.
Pollard, Thomas D.
Pollard, Katherine S.
author_sort Pollard, Daniel A.
collection PubMed
description We provide guidelines for using statistical methods to analyze the types of experiments reported in cellular and molecular biology journals such as Molecular Biology of the Cell. Our aim is to help experimentalists use these methods skillfully, avoid mistakes, and extract the maximum amount of information from their laboratory work. We focus on comparing the average values of control and experimental samples. A Supplemental Tutorial provides examples of how to analyze experimental data using R software.
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spelling pubmed-67246992019-09-06 Empowering statistical methods for cellular and molecular biologists Pollard, Daniel A. Pollard, Thomas D. Pollard, Katherine S. Mol Biol Cell MBoC Technical Perspective We provide guidelines for using statistical methods to analyze the types of experiments reported in cellular and molecular biology journals such as Molecular Biology of the Cell. Our aim is to help experimentalists use these methods skillfully, avoid mistakes, and extract the maximum amount of information from their laboratory work. We focus on comparing the average values of control and experimental samples. A Supplemental Tutorial provides examples of how to analyze experimental data using R software. The American Society for Cell Biology 2019-06-01 /pmc/articles/PMC6724699/ /pubmed/31145670 http://dx.doi.org/10.1091/mbc.E15-02-0076 Text en © 2019 Pollard et al. “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology. http://creativecommons.org/licenses/by-nc-sa/3.0 This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License.
spellingShingle MBoC Technical Perspective
Pollard, Daniel A.
Pollard, Thomas D.
Pollard, Katherine S.
Empowering statistical methods for cellular and molecular biologists
title Empowering statistical methods for cellular and molecular biologists
title_full Empowering statistical methods for cellular and molecular biologists
title_fullStr Empowering statistical methods for cellular and molecular biologists
title_full_unstemmed Empowering statistical methods for cellular and molecular biologists
title_short Empowering statistical methods for cellular and molecular biologists
title_sort empowering statistical methods for cellular and molecular biologists
topic MBoC Technical Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724699/
https://www.ncbi.nlm.nih.gov/pubmed/31145670
http://dx.doi.org/10.1091/mbc.E15-02-0076
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