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Ten simple rules for writing statistical book reviews
Statistical books can provide deep insights into statistics and software. There are, however, many resources available to the practitioner. Book reviews have the capacity to function as a critical mechanism for the learner to assess the merits of engaging in part, in full, or at all with a book. The...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345428/ https://www.ncbi.nlm.nih.gov/pubmed/30677035 http://dx.doi.org/10.1371/journal.pcbi.1006562 |
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author | Lortie, Christopher J. |
author_facet | Lortie, Christopher J. |
author_sort | Lortie, Christopher J. |
collection | PubMed |
description | Statistical books can provide deep insights into statistics and software. There are, however, many resources available to the practitioner. Book reviews have the capacity to function as a critical mechanism for the learner to assess the merits of engaging in part, in full, or at all with a book. The “ten simple rules” format, pioneered in computational biology, was applied here to writing effective book reviews for statistics because of the wide breadth of offerings in this domain, including topical introductions, computational solutions, and theory. Learning by doing is a popular paradigm in statistics and computation, but there is still a niche for books in the pedagogy of self-taught and instruction-based learning. Primarily, these rules ensure that book reviews function as a form of short syntheses to inform and guide readers in deciding to use a specific book relative to other options for resolving statistical challenges. |
format | Online Article Text |
id | pubmed-6345428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63454282019-02-02 Ten simple rules for writing statistical book reviews Lortie, Christopher J. PLoS Comput Biol Editorial Statistical books can provide deep insights into statistics and software. There are, however, many resources available to the practitioner. Book reviews have the capacity to function as a critical mechanism for the learner to assess the merits of engaging in part, in full, or at all with a book. The “ten simple rules” format, pioneered in computational biology, was applied here to writing effective book reviews for statistics because of the wide breadth of offerings in this domain, including topical introductions, computational solutions, and theory. Learning by doing is a popular paradigm in statistics and computation, but there is still a niche for books in the pedagogy of self-taught and instruction-based learning. Primarily, these rules ensure that book reviews function as a form of short syntheses to inform and guide readers in deciding to use a specific book relative to other options for resolving statistical challenges. Public Library of Science 2019-01-24 /pmc/articles/PMC6345428/ /pubmed/30677035 http://dx.doi.org/10.1371/journal.pcbi.1006562 Text en © 2019 Christopher J. Lortie http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Editorial Lortie, Christopher J. Ten simple rules for writing statistical book reviews |
title | Ten simple rules for writing statistical book reviews |
title_full | Ten simple rules for writing statistical book reviews |
title_fullStr | Ten simple rules for writing statistical book reviews |
title_full_unstemmed | Ten simple rules for writing statistical book reviews |
title_short | Ten simple rules for writing statistical book reviews |
title_sort | ten simple rules for writing statistical book reviews |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345428/ https://www.ncbi.nlm.nih.gov/pubmed/30677035 http://dx.doi.org/10.1371/journal.pcbi.1006562 |
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