MINI-LESSON 6: Fooled by Metrics (Correlation)

A maximally simplified presentation of how metrics are random variables, and how they can be gamed. Uncorrelated variables will produce a correlation in samples.
For a more advanced version see the P Values paper:

[jungjunk]

This line pure gold. “The point is not that correlation is not causation but very often correlation is not correlation.”

[tosvarsan]

This the only channel for which I have enabled notifications. I don't want to miss even one of these...

[luccasiaudzionis]

The parts that use Mathematica help tremendously with visualizing the concept. Thanks for these videos!

[nishantjoshi]

Thank you, Professor Taleb, these lessons are proving to be really helpful. Keep up the great work.

[DisfigurmentOfUs]

I find these lessons interesting, they give me some thought food. Thank you, Nikolas.

[DeathFeeble]

I love that we got saved by the bell at the end of the lesson - this is like real school!

[thoms]

Would you have a repository of your mathematica approaches ? Especially if those are illustrated in your book on stat. conseq. of fat tails. I did few on my own but struggled a lot. Thanks

[qlunngx]

I hated Statistics until a friend told me about Prof. Taleb. I love Statistics, thanks Prof.

[malokey]

I sent this to a friend who didn't understand why I hate consultants/analyst or as I like to call them astrologers in suits.

[iqfoot]

I am really happy you are making these. The topics are spot on. I am having trouble following them though - maybe I just don't understand the math enough

[Mindkaiser]

Great insights professor Taleb. Thank you very much.

[frederikstrabo]

Man absolutely love these videos. Do any of you guys know where I could learn more about what he is talking about slope differentials and entropy, like how .1 is closer to 0 than to .2?

[briandenz]

Great video as always, Professor Taleb. Thank you.

[tlturner]

Thank you for the video. What about the aspect of time and space relationship? It seems that the closer two things in time, for example, increases the likelihood for a correlation. For example when troubleshooting an issues, say programming, it's a good idea to check what was last done as it's likely to point to the source of the problem. When looking at the correlation between a tornado and it's damage the closer you are in time and space to the damage is likely the path of the tornado.

[peterevans]

Monte Carlo demonstration is very compelling.

[karanr]

You're probably not going to see this, but would you consider writing and publishing a mathematics and statistics textbook that would teach the subject properly?

[DrGonzaloSaiz]

6:05 Thanks a Lot for this. I love this lectures.

[galerivs]

that is because it calculate it as group of data, not as sequences .... you need to see and calulate based on event time/sequence

[touristatearth]

Thank you for this lesson, it is immensely helpful.

[chuckjones]

You are are most intelligent arab I know.
Shukran!!