This is the oldest, yet often useless, criticism in the world. Statisticians know that when they are observing correlations they don't have statistical evidence for causation. That requires you to take a step back, decide what other variables could cause something, and test for that.
But here it's more than some vacuous claim to correlation.
Do you get unemployed as a BA first, or do you get your BA?
Econometrics is all about identifying causation in correlations in natural data (i.e. you can't run scientific experiments on people's lives, like telling random sample of people to go to college and others to not). Here, you just need intuition to realize that one thing consistently is a prerequisite to another, to realize that it's not just some statistical garbage.
There are three possible models to explain the correlation:
1. Something influences both one's propensity to get more education (E) and not get laid off (L).
2. One's education determines one's propensity to not get laid off
3. One's propensity to not get laid off influences one's education. This is nonsense.
In a Bayesian network, you can visualize 1. as features f0,...fi (say race, parents' income, etc) influencing both (E) and (L), with (E) also influencing (L) directly. 2. would be a set of features f0,...,fi influencing (E) but not (L), with (E) directly influencing (L).
So to conclude, "This chart only shows correlation" is a useless comment to make unless accompanied by an analysis of the possible probabilistic models that the evidence supports.
> "This chart only shows correlation" is a useless comment to make unless accompanied by an analysis of the possible probabilistic models
Correlation implies causality until proven otherwise? Do you work for the government?
> Statisticians know that when they are observing correlations they don't have statistical evidence for causation.
Scientifically inspired voodoo is still voodoo. Say those with higher education have lower employment, you still don't know why. These people could be wealthier than the rest and have better opportunities in life REGARDLESS of their "education" (as one example). The macro-economist would then cite this data point is proof for needing more spending in higher-education, when in reality, this may not be the case.
Correlation implies causality until proven otherwise?
Where did I say that? I said that a comment like "this chart only shows correlation" is as useful as "The sky is blue." The sky is probably blue.
Scientifically inspired voodoo is still voodoo. Say those with higher education have lower employment, you still don't know why. These people could be wealthier than the rest and have better opportunities in life REGARDLESS of their "education" (as one example).
Please refer to the models that such data could support (my previous post). The joint influence of other variables like f0,...,fi is certainly discussed.
The macro-economist would then cite this data point is proof for needing more spending in higher-education, when in reality, this may not be the case.
Please refrain from judging a profession unless it is one that you are familiar with. I mentioned econometrics, which is a specialized form of statistics that focuses primarily on extracting information from observational data.
You claimed OP had no right in claiming causality could not be established unless an opposing data-set was present. Who says this data has to be present? Are econometrics infallible?
You're trying to analyze the human motivation for action in hopes of altering future action, all inside a vacuum void of real-life tests. You claim this type of empirical knowledge is impossible to attain, "(i.e. you can't run scientific experiments on people's lives, like telling random sample of people to go to college and others to not).", but I would disagree.
Companies go to great length to mine data about their customers and their behaviors, with the opportunity to run a-b tests and isolate causal relationships. We should should recognize econometrics for what it is, and that is a theoretical science, and that anyone has the right to question the integrity of claimed causal relationships.
"This is the oldest, yet often useless, criticism in the world."
And criticizing people for pointing out that correlation does not imply causation is the newest, yet often useless, criticism in the world.
Read the context of my statement again. The comment to which I was replying called it "a verifiably sound strategy". Sounds a little strong when the only presented evidence does not control for factors like parents' income (or f0, ... fi as you call them).
Maybe some such evidence does control for those factors, but the evidence presented did not.
So to conclude, "This chart only shows correlation" is a useless comment to make unless accompanied by an analysis of the possible probabilistic models that the evidence supports.
Unemployment certainly isn't the cause of education; Thus if there was a third variable causing both low unemployment and education it must be some intrinsic quality of the individual, such as "hard work" or "intelligence".
Thus it is still good advice to tell students to work hard and do well in school, rather than saying it's okay to be lazy and not pass exams because, well, "education is only correlated with employment prospects".
Not necessarily. Sometimes the better advice is to tell someone to _not_ go to school. Someone who might be a very effective (and well paid) tradesperson, but has no aptitude for University, would be much better served (and probably less stressed) by entering the workforce as young as possible, becoming a journeyman, and raising through their career without a formal education. There are at least three reasons for this:
1. By entering the workforce as young as possible, total lifetimes earnings (and more importantly, savings) are maximized for a longer period of time.
2. If the individual has no aptitude (or desire) for higher education, then there is a very good chance they will neither get the credentials, nor the knowledge that comes with a high level education.
3. Even if they did manage to squeak by and, through sheer grit and determination and stubbornness, acquire the higher education - they might now slot themselves into a field of endeavor for which they are singularly not suited for - only to find 10 years after working some white collar position, that they really, really wished they had been in construction/electrician/blacksmith/what have you...
Frequently the path to maximizing total lifetime earnings, happiness, impact, and productivity is not through higher education. I think that there is a lot of observer bias on most of our part, because most of us have gone through at least some post-high school education and would to believe it generally offers value to those who do likewise.
I've got a least one friend who really should have never gotten his Computing Science degree. He is brilliant in ways that I'll never, ever, match - and should be building houses, not trying to work in IT - just not his gig.
On the flip side, i have a quite comfortable six figure income, and never completed university - I just have an aptitude for working in IT.
I really believe there is a correlation/causation problem with the "Higher educations leads to Higher Income" - the one exception being that a Yale/Stanford/Princeton/Harvard/MIT/Ivy League graduate probably raises the ceiling (and position opportunity) for candidates above what someone without those credentials would have. But now we're talking about the difference between making $150K/year as a mid level manager and $750K/year as a Sr. VP - not as relevant to the masses.
I meant, if you're invited to a high school to talk about raising your employment prospects, it is good idea to tell students to work hard and do well.
There are definitely people who would be better off dropping out as early as possible and start working but that's a minority.
Even electricians and mechanics require tertiary education. (Otherwise, what does my brother training to be a mechanic mean when he says he's going to "class"?!)
Dropping education as early as possible might be a good idea if your aim is to work in a field where knowledge can be easily self taught. (Like IT or painting). Even then, a one year crash course I think would be quite helpful. I self-taught myself programming too, but I only learned about "unit-testing" in university. I guess you can argue I could learn that in my first job, but what if I want to, say, do a startup? ;)
>> I really believe there is a correlation/causation problem with the "Higher educations leads to Higher Income"
We're talking about higher education leads to higher chance of being employed.
Great points, I'm very intelligent and fairly well educated (informally) but have absolutely no use for the University system.
I did exactly that, out of high school into a warehouse job, then tech support, then software engineering, when I look at the cost of student loans, lost work, lost investment opportunities, I put the cost of my BA somewhere around $400,000.
I think maybe you don't understand what correlation means. That the variables of employment and education are correlated means that a change in one variable means that the other variable will change. That is, the two variable change together. It's not necessarily casual relationship but there is a relationship.
That assumes a causal relationship. The chart only shows correlation.