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    Anna Bobrowska said:

    I have just read your first article and though I did recognise all of the concepts presented it still felt good to refresh the memory. I’m eagerly awaiting more.
    I often discuss the need for better statistical training with fellow postdocs and grad students and everyone seems to agree that a “statistics in life sciences” course should be a formal requirement in graduate education. For those of us who are finished with their degrees this column is a great way to improve our understanding of statistics/fill the gaps in statistics knowledge, though I think it should also be a standard for universities and research institutes to offer free statistics training courses aimed especially at post-PhD scientists to rectify their lack of knowledge/fill the gaps.
    As for this column, is there any way to ask for covering specific topics or post comments as to which sections were unclear?

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    David Lovell said:

    I want to applaud Nature for helping emphasise that sound inference from observation is a cornerstone of science. Having worked in quantitative bioscience since 2004, and having had a pretty average introduction to statistics as an undergraduate engineer, I have a lot of sympathy for biologically trained researchers who find statistics challenging… and vice versa.

    The information sciences and the biological sciences are both deep domains, with their own languages and cultures. But these are human constructs, not laws of nature or the universe. So, when we seek to understand nature and the universe through science, I think we would do well to remember that and embrace knowledge from all disciplines in that pursuit. Well done Nature for encourage that interdisciplinary dialogue and understanding through “Points of Significance”

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    Chandan Kumar said:

    Yes, this is a much needed effort…to sensitize and empower the community to the essentials and rigors of statistics in biological experiments. Along these lines, I have often felt that a statistical rigor should be ensured by journals in the peer review of publications as well. Reviewers could be specifically asked if they felt competent to critique on the statistical aspects of the manuscript in question. Also, given the specialized nature of increasingly big data centric research, it may be time the journals got the statistical aspects of manuscripts reviewed through in house statistics experts.