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Comment by TimPC | Hacker News Reader

I find it amusing that the correlation vs causation point has morphed into arguing correlation is anti-causal (which is worse). I think if someone goes from being a doctor to being a bartender their divorce rate might be affected. I saw another data source that said the number one cause of divorce was financial so the correlation may actually be somewhat causal. Financial stress is brutal because it leads to conversations like cutting down on recreation and leisure and reducing spend on hobbies and downtime. This creates a kind of feedback loop where life adds stress and the resources to remove it are taken away because you no longer get to spend $X/month on your recreation because you needed to pay $Z on something else.

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Yes, sure, but the correlation isn't absolute in the first place. As you can see, for instance, clergy members have anomalously low divorce rates for their income level; I'm sure you can imagine why that might be.

Even if their examples are ill chosen I think the point stands if you take two jobs with similar income and a big difference in divorce rate.

The main two reasons for divorce are infidelity and money issues.

So maybe audio engineers have the lowest divorce rates because they make good money and are quite concerned about fidelity? (This is my bad pun for the day).

Watch it, bub. That one should cost you your weekly allotment. ;-)

second time I see humor on hacker news today

is that becoming a trend now?

Source?

google searching "main reasons for divorce" would have given you numerous sources. here's one: https://www.co-oplegalservices.co.uk/media-centre/articles-j...

Life experience. Common sense. Google.

Some regard those as symptomatic of other problems or strongly correlate with other issues e.g. lack of restraint, cultural entitlement, issues with inhibition, poor math skills, societal definition and acceptance of "infidelity", addictions.

Infidelity and money issues are reasons for divorce in the same way that clouds are the reason it rains.

I feel a more valuable explanation would go deeper - into the underlying system that creates the result. In the case of rain, we call it the weather cycle.

Yep, sick of the "correlation is anti-causal". I assume correlation is causal (which is usually the case) until shown otherwise, which this article did not show.

I think assuming correlation is causal is bad as well. But it's a good sniff test. Usually something interesting is going on: sometimes it's A causes B, sometimes its B causes A, sometimes A and B have a common related cause. Sometimes C is non-causal but correlates with A and B and wasn't controlled for. Lots of possibilities.

Correlation is not causation but it's rarely accidental.

Correlation is usually accidental.

e.g. http://www.tylervigen.com/spurious-correlations

Saying that correlation is usually accidental is a stretch. Basing that claim on that (admittedly amusing) website is even more of a stretch: the time series on that website are all highly autoregressive with minuscule sample sizes, which makes spurious correlations extremely likely [1].

Speaking (very) roughly, the fact that they are autoregressive constrains how 'kinky' the shapes can be. Visually speaking, the time series will have a small number of inflection points and will appear interpolated between these points.

This greatly reduces the search space: you just need to line up a couple of kinks in a space of ten samples, or match two smooth and vaguely line-shaped objects, rather than find a convincing relationship for 100s of observations not tied together in time.

[1] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.611...

I've got some homeopathic remedies to sell you. People took them, and they got better!

I think if you measure random unrelated data sets against each other you're quite likely to find spurious correlations. If you design an experiment between potentially related variables with a potential hypothesis on how they are related and then observe data that matches the hypothesis, you probably have a reasonable chance the hypothesis is actually the explanation.

That is the point of experiments.

I see your blog post and raise you a youtube video.

minutephysics Correlation CAN Imply Causation! | Statistics Misconceptions

https://www.youtube.com/watch?v=HUti6vGctQM

Make a list of all the things that have changed over the last century.

My height has increased over the last century.

How many things on that first list are caused by my increasing height? How many caused my increasing height?

Things that have increased over the last century:

- Calories available

- Vaccination rates

- Access to neo-natal care

- Knowledge about fetus and infant development

Correlation is insufficient to prove causation but in many cases it's a great hint.

So as calories available increases, it causes my height to increase?

I'm gonna need a new wardrobe...

You've confused an individual trend with a trend of the aggregate maximum value.

A couple of those may have a minor influence on the limit of my height, but increasing those factors has no effect on my height.

Or how about my age?

And don't forget other highly correlated values, like the number of movies or books published, Chinese population, cumulative deaths in war, and number of artificial satellites. There's a correlation of my age (and height) with each of those.

Just two temporal trends that move in the same direction.

No causation, though.

Most criminals have drunk milk.

Most criminals have been to school.

Most criminals have worn sneakers.

Should we conclude that milk, school and sneakers are causal factors in crime? Should we eliminate these 3 things from society?

I don't think you understand correlation. For crime and milkdrinking to correlate, criminals would need to drink more (or less) milk than non-criminals. A better example would be: umbrella-carrying and windshield-wiping tend to correlate, but they are both actually caused by a hidden factor: rain.

Milk-drinking is not CORRELATED with criminality. Criminals and non-criminals have (as far as I know, but I could be wrong) similar levels of milk-drinking. And so forth.

Unless you are using a different definition of "correlated" than I expect.

There's a website where the author correlates random datasets against each other and displays the ones with really high R values.

http://www.tylervigen.com/spurious-correlations

With today's headline driven media, it's especially important to guard yourself against correlational relationships being implied as causative. It's not about saying whether something is true or false, it's about being skeptical and using the correlation as a starting point for further investigation.

It's unwise to infer causality (which I'm sure you do more carefully than you suggest here) but it's equally unwise to assume independence.

Quite a few of the correlations between random datasets linked by a few posters below, for example, may be explainable by second-order effects.

This is how we get homeopathy and alternative medicine.

Out of the sea of correlations, we find a few drops of causation by analysis and experiment.

> it leads to conversations like cutting down on recreation and leisure and reducing spend on hobbies and downtime

Very good points and I agree with all.

Regarding recreation - I do very well and that conversation can still pop up. My wife doesn't have any hobbies and I have quite a few. I recently got into kayaking so there's a decent upfront cost. She'll make remarks like we need to cut back on spending or you're spending too much, how much was that, etc.

I just tell her - I could cut back on hobbies and spending but that would require me to cut back on work or abandon one of my companies. Then she gets quiet because she knows what that means. :) I also worked the health benefit angle which is always good with wives. She knows I'm going to spend however I want anyway but I try to get her to understand my reasoning and what the benefits are vs the cost.

It's important to enjoy the fruits of your labor and have fun, it's important to have hobbies, and it's important to get exercise.

Certainly you shouldn't spend wrecklessly like some people (take out a HELOC and buy crazy things like dune buggies like so many did in Vegas prior to the collapse), but every couple should save a set percentage (ideally 10%+) and have a discretionary budget. That way you don't get all the passive aggressive remarks and arguments when one of you spends money on themselves. It's already been decided.

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