randy.pub
Analytics at presagegroup.com | PhD Epidemiology | #julialang #rstats | publications at www.randy.pub | GitHub @rdboyes, currently working on https://github.com/TidierOrg/TidierPlots.jl | š¦@randyboyes
137 posts
366 followers
450 following
Getting Started
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Unless I'm misunderstanding what you want, it does already - you just have to use the ...
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It's not an inherent property of the task, no - e.g. here's an example in julia that does the same thing but has the expected variance in the last digits
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Itās the 17 squares all over again
Why would you put this evil in my brain this early in the morning
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This is probably the right answer, but itās a little unsatisfying
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This was my first thought too! I would have only been half-happy if it worked though - itās neat but wouldnāt look exactly like the target, which is the goal
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XCOM does this as well, but only on the lower difficulties. On the higher ones, the probability it shows is the one it uses, and it feels brutal
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Iām willing to give it a try!
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It's more broad than that - it just means "the best existing measure" for anything, not causality specifically
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[1] 100 2 3 4 5 6 7 8 9 10
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This is mandatory DLC we all install in our early 30ās, unfortunately
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Yes until very no
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Yeah Iāll make an exception for Excel and half of one for GitHub but Teams is so bad I feel like it cancels those out
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This but for all Microsoft products
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They're "hack-proof and secure", obviously
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Not to mention that it might be easier to get people to agree to review papers if they had a focused objective to review a specific part of the paper
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Fair - but I think I personally would be more confident in the results of a paper with one code review and one methods review vs two methods and zero code
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Professional programmers are estimated to introduce around 50 bugs per 1000 lines of code, 10 of which make it through checks
How many bugs are scientists (amateur programmers at best) letting through without checks?
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Not every reviewer would have to be an expert in every area though. Someone from a related discipline who knows R well could easily check if the code matches what they said they did in the paper, catch data cleaning errors, etc even if they canāt comment on the subject matter
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Haha I wrote it, hit reply, then googled āveil of ignoranceā to see if it made sense or not :)
I think youāre right
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Maybe you donāt but I pre-register my studies from behind the veil of ignorance
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I'm bookmarking this for reference since R's NSE stuff always throws me off!
One of the nice things about working in @tidierjl.bsky.social is that you can drop down into #julialang at any time, which has a nice division between "normal evaluation" and "shenanigans":
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Yes
But as soon as you need to collaborate with someone who ādoesnāt want to see the codeā the whole thing falls apart
Currently sanding off the rough edges of a typst.app based workflow for report-writing, itās pretty promising but thereās still some pain
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I think this is it - the perfect data visualization
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You can cut one more pixel if you're willing to assume you can interpolate to get blank points
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Cut the intermediate braille labels for even more information density! (people should of course be able to infer that the categories are in alphabetical order between a and g ;) )
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Journalists publish corrections for small errors that do not change their conclusions all the time. Textbooks have errata. I donāt see what the issue is with having a mistake - no matter how trivial - corrected online, as long as it is actually a mistake, which it seems like you are not disputing
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I will concede that that particular mistake does not seem important
But it is a mistake, and there is no reason for it not to be on pubpeer. If it was the only comment on the paper, my own response would be to have increased confidence in the results as a result of its pubpeer page
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I donāt know whether the comments posted on pubpeer are accurate. I havenāt looked into it. But the frequency of comments, number of accounts per individual, whether or not different commenters know each other, and everything else in that āarticleā are all irrelevant to that question.
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The rate of reporting is not relevant - are there problematic images in your papers?
If you think she is wrong, say that. Demonstrate that even one of these reports is fabricated/incorrect and you may get some sympathy
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I donāt see any problem with scaling the data here
If the rate on the right axis was āper 20,000ā they could be the same numbers, but I donāt think that would improve the graph in any meaningful way
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The org that does this for Ontario is called ICES, and thereās some basic info on their site: www.ices.on.ca/data-privacy/
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Good to know, bad to use (unless there is not other option)
The code in the screenshot could be replaced with map call and would be much clearer
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Considering the millions that are spent to eke out a couple extra percentage points on benchmarks, it seems ridiculous to argue that 0.06% is a meaningless number. 100 or so of the right books and weāre talking about the difference between state of the art and ānot in the runningā
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I believe
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Me, using both -> and <- for assignment in the same script
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Season 1 is great, the rest is pretty forgettable
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I typically do this with a loop and knitr::knit_child - all of my examples are code I canāt share but I can write an example if you need/want more detail