What haunts statisticians at night

preview_player
Показать описание

We all want cause and effect, but there's something that will almost always get in the way of well-meaning statisticians.

🔗 LINKS MENTIONED:

OTHER CHANNEL LINKS

This video was sponsored by Brilliant.
Рекомендации по теме
Комментарии
Автор

forgot to pin this, don't shame me Brilliant lol

very-normal
Автор

My favourite example of differentiating correlation and causation is that even though firefighters and housefires are often seen together, it's pretty clear the fire department didn't cause the fire

Vaeinoe
Автор

A couple years ago I read a survey of sci-comm articles that actually found they were too conservative on describing things as correlation/causation. People had the correlation =/= causation warning drilled into them to the point that they were describing results which by the study design could be attributed to causation as "just" correlation!

AmberSZ
Автор

As someone in social science (public policy), this is constantly on my mind. 'All of Statistics' has great chapters on causation and DAGs, even covering continuous causal variables. It also points to other great sources on causal analysis for anyone curious.

blakaligula
Автор

I like how you quote the cartoon _The Boondocks_ about unknown unknowns, in the part where they quote Donald Rumsfeld who was paraphrasing NASA administrator William Graham, who was referencing the work of Joseph Luft and Harrington Ingham's work developing the Johan window in 1955.

I love how real expert research gradually enters the pop culture zeitgeist!

BradyPostma
Автор

One of the best explanations on basic concepts which also sheds light on the intricacies related..

shreeniwaz
Автор

please, PLEASE don't stop doing these videos! I love them!

florentinudrea
Автор

Genuinely loving the stuff here about theory and practice. Keep it up!

InOtherNews
Автор

Just some words auf caution about the statement "causation implies correlation". This does of course not mean that a strong linear bivariate correlation is necessary for a causal effect. Confounders can also push the empirical correlation close to 0 with there still being a causal effect

figmundsreud
Автор

I have a quibble: causation often involves correlation, but there are situations where it doesn’t. You have to take the functional form into account as well. For example, if the underlying function is a more or less symmetric "U"-shaped one (e.g. a quadratic one) over the range for which you have data, you can have strong causal relation with little or no correlation (which is designed to assess linear relationships but can also detect monotonic ones, albeit with a loss of accuracy/"explanatory power").

Obviously, the equivalent of the correlation coefficient in a general regression model (one that takes account of real non-linear interaction effects), the R-square, does enable you to get a good sense of the explanatory power of non-linear relationships - albeit not without their own issues with confounding factors. But it remains somewhat misleading to assert a clear one-way relationship between causality and "correlation".

PeloquinDavid
Автор

I needed this explanations long time ago! Thanks. I loved the simulations to show the impact of ‘C’

andresfelipehiguera
Автор

Hi, I just want to say that you and your videos are a blessing to me and many others! Cheers man!

Agent-cipher-
Автор

That boondock's clip lol.
This is probably my favorite stats page.
Keep doing what you're doing.

justdave
Автор

I’m so glad I double-majored with a stats concentration… This was one of the best things I covered in our undergrad ANOVA course.

superuser
Автор

YOU TRICKED ME I subliminally absorbed your “example” of clicking this video to SUBSCRIBE, to see what effect there was, and now I am subscribed!!! (Happily 😊 )

requetevision
Автор

This is the best explanation of a counterfactual I've heard. Made it very simple. 🎉

dumbpenguin
Автор

My question is, if excluding confounders leads to ommitted variable bias and including confounders leads to multicollinearity (due to the high correlation between the confounder variable and the other explanatory variable/s), what can one do?

lok
Автор

As a statistician i wanna say "congrats and thank you too had shared such a great video🎉🎉

sitrakaforler
Автор

I know this might be a silly question, but is your voice ai-gen? It just sounds so much like it, especially at 1:47. Sorry, if it isn't, that's my bad.

allieindigo
Автор

It keeps them up at night the way those confounding Dover Boys drove that one guy to drink!

travisretriever