858
answer = sum(n) / len(n)
(lemmy.eco.br)
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 08 Jul 2024
858 points (96.8% liked)
Science Memes
11416 readers
2304 users here now
Welcome to c/science_memes @ Mander.xyz!
A place for majestic STEMLORD peacocking, as well as memes about the realities of working in a lab.
Rules
- Don't throw mud. Behave like an intellectual and remember the human.
- Keep it rooted (on topic).
- No spam.
- Infographics welcome, get schooled.
This is a science community. We use the Dawkins definition of meme.
Research Committee
Other Mander Communities
Science and Research
Biology and Life Sciences
- !abiogenesis@mander.xyz
- !animal-behavior@mander.xyz
- !anthropology@mander.xyz
- !arachnology@mander.xyz
- !balconygardening@slrpnk.net
- !biodiversity@mander.xyz
- !biology@mander.xyz
- !biophysics@mander.xyz
- !botany@mander.xyz
- !ecology@mander.xyz
- !entomology@mander.xyz
- !fermentation@mander.xyz
- !herpetology@mander.xyz
- !houseplants@mander.xyz
- !medicine@mander.xyz
- !microscopy@mander.xyz
- !mycology@mander.xyz
- !nudibranchs@mander.xyz
- !nutrition@mander.xyz
- !palaeoecology@mander.xyz
- !palaeontology@mander.xyz
- !photosynthesis@mander.xyz
- !plantid@mander.xyz
- !plants@mander.xyz
- !reptiles and amphibians@mander.xyz
Physical Sciences
- !astronomy@mander.xyz
- !chemistry@mander.xyz
- !earthscience@mander.xyz
- !geography@mander.xyz
- !geospatial@mander.xyz
- !nuclear@mander.xyz
- !physics@mander.xyz
- !quantum-computing@mander.xyz
- !spectroscopy@mander.xyz
Humanities and Social Sciences
Practical and Applied Sciences
- !exercise-and sports-science@mander.xyz
- !gardening@mander.xyz
- !self sufficiency@mander.xyz
- !soilscience@slrpnk.net
- !terrariums@mander.xyz
- !timelapse@mander.xyz
Memes
Miscellaneous
founded 2 years ago
MODERATORS
Just because you don't know what the uncertainties are doesn't mean they're not there.
Most optimization problems can trivially be turned into a statistics problem.
Sure if you mean turning your error function into some sort of likelihood by employing probability distributions that relate to your error function.
But that is only the beginning. Apart from maybe Bayesian neural networks, I haven't seen much if any work on stuff like confidence intervals for your weights or prediction intervals for the response (that being said I am only a casual follower on this topic).
One of the better uses I've seen involved using this perspective to turn what was effectively a maximum likelihood fit into a full Gaussian model to make the predicted probabilities more meaningful.
Not that it really matters much how the perspective is used, what's important is that it's there.