Timeline for Correlation between sine and cosine
Current License: CC BY-SA 3.0
17 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| S Jul 17, 2016 at 19:22 | history | suggested | Rodrigo de Azevedo | CC BY-SA 3.0 |
Minor edits
|
| Jul 17, 2016 at 18:42 | review | Suggested edits | |||
| S Jul 17, 2016 at 19:22 | |||||
| S Jul 17, 2016 at 15:32 | history | suggested | J. M. is not a statistician | CC BY-SA 3.0 |
some formatting tweaks
|
| Jul 17, 2016 at 15:09 | review | Suggested edits | |||
| S Jul 17, 2016 at 15:32 | |||||
| Jul 16, 2016 at 23:27 | history | tweeted | twitter.com/StackStats/status/754457416469798912 | ||
| Jul 16, 2016 at 21:34 | answer | added | Matthew Drury | timeline score: 13 | |
| Jul 16, 2016 at 21:22 | vote | accept | uklady | ||
| Jul 16, 2016 at 20:42 | comment | added | Chris | Well they are lagged correlated and each one is autocorrelated with itself! | |
| Jul 16, 2016 at 18:50 | comment | added | whuber♦ | If you do that, then you only need draw a scatterplot--no integration is necessary. That scatterplot is a uniform distribution on the unit circle (obviously). Since the circle is symmetric under any reflection through the origin, the correlation equals its negative, whence it must be zero, QED. | |
| Jul 16, 2016 at 16:50 | history | edited | Kodiologist | CC BY-SA 3.0 |
Added the more precise question decided upon in the comments.
|
| Jul 16, 2016 at 16:46 | answer | added | Kodiologist | timeline score: 24 | |
| Jul 16, 2016 at 16:23 | comment | added | uklady | Maybe I could take $[0, 2*pi]$ as the support (I would be assuming that $f=1$, so the interval contains one full cycle). I guess the integration problems will then vanish as well | |
| Jul 16, 2016 at 16:21 | comment | added | Kodiologist | So you want $X$ uniformly distributed and then you define $Y = \sin X$ and $Z = \cos X$? That's fine except you also need to specify the support of $X$'s density, since there is no uniform distribution over the whole of $ℝ$, or any other infinitely long interval. | |
| Jul 16, 2016 at 16:18 | comment | added | uklady | If I assume time is a uniform random variable ($X$ in my text), is it not possible to do this? I mean I would be then looking at the correlation of two transformed random variables. | |
| Jul 16, 2016 at 16:16 | comment | added | Kodiologist | As stated, your problem is insufficiently defined. Correlation is a concept that applies to random variables, not functions. (Formally, a random variable is a kind of function, namely a measurable function from a probability space to the real numbers equipped with the Borel measure. But just saying "the sine function" doesn't tell you anything about the probability measure in the domain, which is what gets you probabilistic information, including joint distributions.) | |
| Jul 16, 2016 at 16:11 | review | First posts | |||
| Jul 16, 2016 at 16:25 | |||||
| Jul 16, 2016 at 16:06 | history | asked | uklady | CC BY-SA 3.0 |