Best of Twitter - Week of June 22, 2020 - how to account for free tech services in GDP?
Interesting! Quote:
"The median estimates from a 2017 choice experiment in rank of highest to lowest were search engines ($17,530), email ($8,414), digital maps ($3,648), video streaming ($1,173), e-commerce ($842), social media ($322), music ($168), & instant messaging ($155)."
Erik Brynjolfsson @erikbryn
"Science isn’t the sum of what scientists think. Had science operated by majority consensus we would be still stuck in the Middle Ages and Einstein would have ended as he started, a patent clerk with fruitless side hobbies." — Nassim Nicholas Taleb
"Scientists set out to replicate 53 landmark studies... for new approaches to treat cancers. They were able to replicate the findings only 11% percent of the time."
It's not a reproducibility crisis in PSYCHOLOGY. It's a reproducibility crisis in SCIENCE.
2/ It's cancer research, it's heart disease research, it's psychology—it's EVERY AREA OF BIOMEDICAL RESEARCH any reproducibility project has examined.
Psychology was exposed 1st because and only because psychology experiments are cheap/easy to reproduce.
@DellAnnaLuca @aroraharshita33 A goal or target can be useful even if disregarded, because it makes one’s ideas clear enough to be contradicted later, and that allows one to improve them.
All progress starts with a conflict between ideas.
^ hard to remember a tweet that influenced me more than this one
can't stop thinking about this
>why does anyone walk up to a mass-execution trench and kneel to be shot? forum.guzey.com/t/why-do-peopl…
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Alexey Guzey @alexeyguzey
BTW @hierarchon reminded me of a neat trick with saccadic masking: go look in a hand mirror. no matter how close you bring it to your eyes, and how much you look around, you will never see your eyes move.
You're blind during those moments. But you still think you are seeing.
Quarantined Section
"[in] group who read the information on a logarithmic scale...only 40.66%...could respond correctly to a basic question about the graph (whether there were more deaths in one week or another), contrasted to 83.79% of respondents on the linear scale."
Study authored by 12 people from Yale, including the Director of Yale Institute for Global Health who is also an infectious disease epidemiologist:
This graph is amazing. It shows that measuring #SARSCoV2 levels in municipal sewage almost perfectly predicts forthcoming #COVID19 cases with a full week's notice (R=0.994). It's one of several discoveries in this new study from @Yale: medrxiv.org/content/10.110…. C-19 is #InThePoop
This preprint is getting a lot of likes and retweets. But a correlation of .994 when one of the variables is an integer in the range (0,29) seems... optimistic. /1
Brennan Spiegel, MD, MSHS @BrennanSpiegel
The data don't seem to be readily available, so I digitised them by eye from Figure 2A. This will certainly be imperfect, but it's quite easy to calibrate the red [virus] dots, since the grey [admissions] dots must be integers. /2
Here are the results. Not quite 0.994. And the largest correlation is on the day after the samples were taken (whereas the preprint says the best results were found after 3 days). /6
^ It turns out the authors reported the correlation from smoothed data (as on the first picture), not raw data (as on the second picture). Here’s a simple way you could’ve realized that study is bullshit: correlations of 0.994 don’t exist in the real world.