The second handbook is taking shape

A preprint of a new handbook titled R for Photobiology is now available. Only a few pages are based on Beyond the Visible, the handbook produced during COST Action FA0906 UV4growth. Everything else is new material. As authors we have decided to publish it before it is finished, so that we can make changes and additions based on your comments. It is available through Leanpub. For dowloading the PDF, whether you decide to pay for it or not, you will have to register as user of the Leanpub the site. You will only receive an occasional message from the authors of the book you have downloaded when a significant update to the books become available. And you will be able to opt-out from receiving them. Hoping that you will find the handbook useful, and looking forward to your suggestions for improvements!   Share this

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Follow-up to the statement on p-values by ASA

The American Statistical Association Says [Mostly] No to p-values Norman Matloff has published a new post after receiving criticism and comments about stating “The ASA says No to p-values” in his post I wrote about some days ago. He defends his interpretation in this new post. However, I think, the interpretation of  the statement in a context different from the “Big data” field to which he is used to does not need to always be “Says No to p-values” but instead in many cases could be “Use p-values to assess the strength of the evidence and nothing else”.  However, “tests” with binary outcomes on probabilities that are essentially continuous, will always be based on an arbitrary threshold and discard a great deal of information. Consequently to me using as suggested by Norman Matloff  “assess” in place of “test” makes a lot of sense. The new post is at https://matloff.wordpress.com/2016/03/09/further-comments-on-the-asa-manifesto/ “Itʹs Not The P-valuesʹ Fault” Joint post by Yoav Benjamini and Tal Galili. The post highlights points raised by Yoav in his official response to the ASA statement… Source: It’s Not The P-values’ Fault – Reflections On The Recent ASA Statement (+relevant R Resources) | R-statistics Blog P-values: the Continuing Saga I highly recommend the blog post by Yoav Benjamini and…

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The American Statistical Association Says No to p-values

This post is copied from my Blog for Students and is to some extent off-topic but relevant to anybody doing research. Norman Matloff (2016) writes in his post: Sadly, the concept of p-values and significance testing forms the very core of statistics. A number of us have been pointing out for decades that p-values are at best underinformative and often misleading… Source: After 150 Years, the ASA Says No to p-values | Mad (Data) Scientist Yesterday, the statement by the American Statistics Association was published on-line in the journal “The American Statistician”. Many statisticians have been aware of the problems of significance tests for a long time, but general practice, teaching and journal instructions and editors’  requirements had not changed. Let’s hope the statement will start real changes in everyday practice. John W. Tukey (1991) has earlier written quite boldly about the problem: Statisticians classically asked the wrong question—and were willing to answer with a lie, one that was often a downright lie. They asked “Are the effects of A and B different?” and they were willing to answer “no.” All we know about the world teaches us that the effects of A and B are always different—in some decimal place—for any A and B. Thus…

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