[Taxacom] Taxacom Digest, Vol 180, Issue 1

m7876 m7876 at mail.ru
Thu Apr 1 20:54:55 CDT 2021

Dear Santiago,
I think that you already received two best advices: (1) have some own work to do with R and (2) copy/paste/play with the code. I was in similar position in the beginning of 2000s but there were no Coursera or stackoverflow these times so (1) and (2) really helped me.
But then I decided to help others so there is a book and video channel. Book is here:  http://ashipunov.info/shipunov/school/biol_240/en/visual_statistics.pdf ; book materials here  http://ashipunov.info/shipunov/software/r/r-en.htm , associated class materials here http://ashipunov.info/shipunov/school/biol_240/ , they also made book online by chapters here https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_Visual_Statistics_Use_R_(Shipunov) . Book might be too big so there is Appendix A «for the impatient readers», kind of example R session (initially written by Polina Volkova). It was really helpful to my students. Better way however is to read the book, answer questions and study supplied answers. You can also use our laboratories from here http://ashipunov.info/shipunov/school/biol_240/lab_all.pdf .
Channel  https://www.youtube.com/channel/UC2X8 o XgT4oO24RlMW1kCR52A/videos?view=0&sort=da&flow=grid is more strict, it is about «machine learning» (in the very broad sense) but might be useful to those who prefer learning from videos. If you decide to go this way, I would recommend to start from older videos and go towards newer ones.
Needless to say is that (nearly) all examples are biological, I simply cannot think of anything else :) And please do not worry that things are going slow. I am in Japan for more than one year but still cannot buy the breakfast entirely in Japanese :))
With best wishes,
Alexey Shipunov
>Четверг, 1 апреля 2021, 20:01 +03:00 от taxacom-request at mailman.nhm.ku.edu:
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>Today's Topics:
>   1. Learning R fast: Any recommendations? (Jorge A. Santiago-Blay)
>   2. Re: Learning R fast: Any recommendations? (Martin Fikáček)
>   3. Re: Learning R fast: Any recommendations? (Mario Schädel)
>   4. Re: [EXT] Re: Learning R fast: Any recommendations?
>      (Mary Barkworth)
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