Timeline for Question about information measurement for continuous random variable
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 5, 2022 at 8:52 | comment | added | Jojo | I thought the point was that, $Y$ is more spread out than $X$. This means that when we sample from $X$ we know more about what result we're going to get (ie. it will likely be closer to the mean value) than when we sample from $Y$. Hence sampling from $Y$ gives more information, as we knew less about what we'd get prior to sampling | |
| Apr 5, 2022 at 8:47 | answer | added | The_Sympathizer | timeline score: 18 | |
| Apr 5, 2022 at 5:50 | history | became hot network question | |||
| Apr 5, 2022 at 2:40 | comment | added | Buzz | 1) Gian-Carlo Rota frequently pointed out that addressing this kind of behavior for the entropy of continuous probability distributions was one of the biggest outstanding problems in applied mathematics. 2) For the entropy of physical systems, like gasses, it turns out that a factor of $\hbar$ shows up seemingly out of nowhere to fix the problem. | |
| Apr 5, 2022 at 1:50 | answer | added | Paul Siegel | timeline score: 21 | |
| S Apr 4, 2022 at 21:50 | review | First questions | |||
| Apr 5, 2022 at 2:08 | |||||
| S Apr 4, 2022 at 21:50 | history | asked | Icarus | CC BY-SA 4.0 |