Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Seven basic rules for causal inference

pedermisager.org

Post reply on HN
Print view View original

61–70 of 71 posts

Re: Seven basic rules for causal inference

#61

Post by jerf »

geye1234 wrote: post #34
jerf wrote: post #21

Earlier quoted context omitted.

"correlation does not imply causation is wrong" That's a specific instance of a more general problem in the "logical fallacies", which is that most of them are written to be true in an absolutist, Aristotelian frame. It is true that if two things are correlated you can not therefore infer a rigidly 100% chance that there is a causative relationship there. And that's how Aristotelian logic works; everything is either…

I don't disagree with the substance of your comment, but want to clarify something. Lesswrong promulgated a seriously misleading view of Aristole as some fussy logician who never observed reality and was unaware of probability, chance, the unknown, and so on. It is entirely false. Aristotle repeats, again and again and again, that we can only seek the degree of certainty that is appropriate for a given subject matter…

I consider Aristotelian logic to be a category. It is the Newtonian physics of the logic world; if your fancier logic doesn't have some sort of correspondence principle to Aristotelian logic, something has probably gone wrong. (Or you're so far out in whacky logic land you've left correspondence to the real universe behind you. More power to you, as long as you are aware you've done that.) And like Newton, being the first to figure it out labels Aristotle as a certifiable genius.

See also Euclid; the fact that his geometry turns out not to be The Geometry does not diminish what it means to have blazed that trail. And it took centuries for anyone to find an alternative; that's quite an accomplishment.

If I have a backhanded criticism hiding in my comment, it actually isn't pointed at Aristotle, but at the school system that may teach some super basic logic at some point and accidentally teaches people that's all logic is, in much the same way stats class accidentally teaches people that everything is uniformly randomly distributed (because it makes the homework problems easier, which is legitimately true, but does reduce the education's value in the real world), leaving people fairly vulnerable to the lists of fallacies they may find on the internet and unequipped to realize that they only apply in certain ways, in certain cases. I don't know that I've ever seen such a list where they point out that they have some validity in a probabilistic sense. There's also the fallacies that are just plain fallacious even so, but I don't generally see them segmented off or anything.

Re: Seven basic rules for causal inference

#62

Post by 082349872349872 »

jerf wrote: post #61
geye1234 wrote: post #34

Earlier quoted context omitted.

I don't disagree with the substance of your comment, but want to clarify something. Lesswrong promulgated a seriously misleading view of Aristole as some fussy logician who never observed reality and was unaware of probability, chance, the unknown, and so on. It is entirely false. Aristotle repeats, again and again and again, that we can only seek the degree of certainty that is appropriate for a given subject matter…

I consider Aristotelian logic to be a category. It is the Newtonian physics of the logic world; if your fancier logic doesn't have some sort of correspondence principle to Aristotelian logic, something has probably gone wrong. (Or you're so far out in whacky logic land you've left correspondence to the real universe behind you. More power to you, as long as you are aware you've done that.) And like Newton, being the…

> ...it took centuries for anyone to find an alternative...

Pedantry: s/centuries/millennia/ (roughly 21 of the former, 2 of the latter?)

EDIT: does anyone remember the quote about problems patiently waiting for our understanding to improve?

Re: Seven basic rules for causal inference

#63

Post by throwway_278314 »

curiousgal wrote: post #56
nomilk wrote: post #55

Humble reminder of how easy R is to use. Download and install R for your operating system: https://cran.r-project.org/bin/ Start it in the terminal by typing: R Copy/paste the code from the article to see it run!

Can't use R without RStudio. It so much better than the terminal.

really??? I've developed in R for over a decade using two terminal windows. One runs vim, the other runs R. Keyboard shortcuts to send R code from vim to R.

first google hit if you want to try this yourself: https://www.freecodecamp.org/news/turning-vim-into-an-r-ide-...

Sooooooo much better than "notebooks". Hating on "notebooks" today.

Re: Seven basic rules for causal inference

#64

Post by carlmr »

nomilk wrote: post #55

Humble reminder of how easy R is to use. Download and install R for your operating system: https://cran.r-project.org/bin/ Start it in the terminal by typing: R Copy/paste the code from the article to see it run!

>Humble reminder of how easy R is to use.

I had to learn R for a statistics course. This was a long time ago. But coming from a programming background I never found any other mainstream language as hard to grok as R.

Has this become better? Is it just me that doesn't get it?

Re: Seven basic rules for causal inference

#65

Post by crystal_revenge »

> Independent variables are not correlated

But it's important to remember that dependent variables can also be not correlated. That is no correlation does not imply independence.

Consider this trivial case:

X ~ Uniform(-1,1)

Y = X^2

Cor(X,Y) = 0

Despite the fact that Y's value is absolutely determined by the value of X.

Re: Seven basic rules for causal inference

#66

Post by crystal_revenge »

islewis wrote: post #37
jdhwosnhw wrote: post #36

Earlier quoted context omitted.

This isnt a correction to your post, but a clarification for other readers: correlation implies dependence, but dependence does not imply correlation. Conversely, two variables share non-zero mutual information if and only if they are dependent.

Could you give some examples of dependence without correlation?

I mentioned it in another comment, but the most trivial example is:

X ~ Unif(-1,1)

Y = X^2

In this case X and Y have a correlation of 0.

Re: Seven basic rules for causal inference

#67

Post by incognito124 »

nomilk wrote: post #55

Humble reminder of how easy R is to use. Download and install R for your operating system: https://cran.r-project.org/bin/ Start it in the terminal by typing: R Copy/paste the code from the article to see it run!

R is my least favorite language to use, thanks to the uni courses that force it

https://github.com/ReeceGoding/Frustration-One-Year-With-R

Re: Seven basic rules for causal inference

#68

Post by TheRealPomax »

crystal_revenge wrote: post #65

> Independent variables are not correlated But it's important to remember that dependent variables can also be not correlated . That is no correlation does not imply independence. Consider this trivial case: X ~ Uniform(-1,1) Y = X^2 Cor(X,Y) = 0 Despite the fact that Y's value is absolutely determined by the value of X.

This is also why it's important to look at your plots. Because simply looking at your scatter plot makes it really obvious what methods you can't use, even if it doesn't really tell you anything about what you should use.

Re: Seven basic rules for causal inference

#69

Post by antognini »

crystal_revenge wrote: post #65

> Independent variables are not correlated But it's important to remember that dependent variables can also be not correlated . That is no correlation does not imply independence. Consider this trivial case: X ~ Uniform(-1,1) Y = X^2 Cor(X,Y) = 0 Despite the fact that Y's value is absolutely determined by the value of X.

The author is using "correlation" in a somewhat non-standard way. He isn't referring to linear correlation as you are, but any sort of nonzero mutual information between the two variables. So in his usage those two variables are "correlated" in your example.
Post reply on HN