As someone who uses and teaches R extensively (and loves the tidyverse) the tidyverse is so much easier to teach to people without any programming experience and who have very little faith in their tech or maths skills (which was me as well).
The tidyverse just 'made sense' to me when I started using R for the first time a few years ago, and now I love using R and programming. On the other hand, some of my ex-classmates learnt base R (because that's what we were taught) and found it hard, didn't learn anything properly, and now still think R or other programming languages are opaque and hard.
I'm not particularly fussed if Statistics Profs prefer data.table to dplyr or base R to tidyr, I know what is easier to teach, understand and use for me and a lot of other ecology/bio students and people.
I'd always (and always do) google an advert rather than trying to remember the exact website anyway. If you search 'href sep' or 'hrefs seo' or even 'aref seo' it always still comes up as the first result for me.
So this is the research area that I currently work in, albeit with a disease ecology perspective rather than a biochemistry one. I've had a quick read of it and and although it does seem to track other research that has been done ("Why are behavioral and immune traits linked?" by Lopes 2017 is a nice review) I'd love to see some power analyses - the sample size seems pretty small for something as complex as this question. The study I'm helping with now has a minimum sample size in the hundreds, for instance, for a broadly similar question. PCA-ing a few tests together is pretty common, but also comes with a lot of potential biases (see "Avoiding the misuse of BLUP in behavioural ecology" by Houslay and Wilson if anyone is interested!)
It's great that this has been picked up recently, it's something I've been following along with for a while. If anyone is interested, James Heathers runs a podcast called Everything Hertz (https://twitter.com/hertzpodcast) with Dan Quintana and Nick has been a guest on it - it's well worth listening to if you're interested in science full stop.
These guys aren't researchers in my area of interest but the topics they cover are interesting and done very entertainingly!
I'm pretty sure they would be able to - I worked with cancer trial data (just a student job, doing data entry) but all patients were completely anonymised to anyone working with the data but readily identifiable by a specific unique ID number, so higher-level trial managers and doctors could find patient information if needed.
I love Chance, but I can't imagine that he's got the net worth already himself to buy SoundCloud / make a meaningful investment - maybe he has contacts who do or could help an investment group, but I think it might be a bit fanciful to say that Chance by himself can save SoundCloud.
Not a huge amount of experience with models this big, but a common problem I see in Ecology is a bit of a misunderstanding of how models can be used - they're only really useful as a representation of what is going on and a way of trying to look at a few variables.
A lot of the time models are seen as a kind-of black box, where you stick data in and get the right data out - doesn't quite work that way!
That is true, they do, but in the UK at least all new ones/sites do need full ecological impact assessments (there are various levels of assessment needed depending on habitat suitability) and hopefully there will be a lessening on the problem long-term - off-shore is the way to go, of course!
I get why they've done it, and The Guardian is a site that I both contribute to and disable my ad-blocker for, but I will miss the speed at which the articles load on my ancient and rubbish phone.
The tidyverse just 'made sense' to me when I started using R for the first time a few years ago, and now I love using R and programming. On the other hand, some of my ex-classmates learnt base R (because that's what we were taught) and found it hard, didn't learn anything properly, and now still think R or other programming languages are opaque and hard.
I'm not particularly fussed if Statistics Profs prefer data.table to dplyr or base R to tidyr, I know what is easier to teach, understand and use for me and a lot of other ecology/bio students and people.