Ten simple rules for writing statistical book reviews
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computer Education, Data Science, Programming Languages
- Keywords
- writing reviews, ten simple rules, statistics books, R programming language, eresources, pedagogy, critical thinking, writing, statistics, computational biology
- Copyright
- © 2018 Lortie
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Ten simple rules for writing statistical book reviews. PeerJ Preprints 6:e26924v1 https://doi.org/10.7287/peerj.preprints.26924v1
Abstract
Statistical books are an opportunity for accessing relatively deeper insights into statistics and software even outside the introductory classroom setting. There are however many resources available to the practitioner in addition to the traditional text model. Book reviews can thus provide a critical mechanism for the learner to assess whether the commitment to a specific book warrants the allocated time and effort. The ten simple rules format, pioneered in computational biology, was applied here to writing effective book reviews for statistics because of the breadth 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 statistical challenges.
Author Comment
This is a pre-print.