Creativity Predicts a Longer Life
scientificamerican.com
scientificamerican.com
http://www.ocf.berkeley.edu/~johnlab/2008chapter.pdf
and "openness" is the most poorly defined of the five personality factors in the model. It is plain, on stronger and better replicated evidence, that the factor "neuroticism" is a risk factor for many bad outcomes, including shorter lifespan. Some investigators have proposed specific interventions to reduce neuroticism in the general population.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2792076/
The relationship of "openness" to creativity is still debatable, and still more debatable is the relationship of openness (or creativity) to mortality.
I should also note that the study described in the article kindly submitted here doesn't allow for the causal inference, or verify the proposed mechanism, made in the quoted statements in the article.
Many external causes are known to negatively effect both creativity and life-span. Most chronic illnesses reduce both. Alcoholism reduces both. Genetic disorders such as Down's syndrome or Huntington's reduce both.
Given many known mechanisms for external factors causing both factors in a correlation study, and only speculative mechanisms for how one factor causes the other, even hinting at causation is bad journalism.
REALLY? What do you WANT them to say? Accuracy of a prediction implies some sort of causal relationship, but not a direct one by any means. All of the thing you suggest are causal links. A genetic disorder causing a decrease in both lifespan and creativity is causation. "A predicts B" does NOT AT ALL imply "A causes B" - tinsel, wreaths, and increased toy buying predict Christmas.
If you're not convinced that the reporters are trying to suggest causation with the word "predicts", try swapping the two terms. Would they write a headline, "Longer life predicts creativity"?
Also it could be that some long living people are creative and all creative people are long living; while creative still not being a cause of the longer life. (let's say all creative people eat peanut butter sandwiches, and it was infact the peanut butter that caused a longer life.)
"The weatherman predicts the weather". Are you saying in this sentence, causation is implicitly referenced?
...
That said, if I was looking at records of the deceased and first discovered a person's age at time of death, then I could use the correlation to predict that I am likely to further find that they were creative.
> REALLY?
Yes -- really. It is very misleading.
> What do you WANT them to say?
Replace "predicts" with "is correlated with." That's the meaning of the work being described -- a correlation between A and B has been observed. But this doesn't mean that A predicts B, or A causes B, or even that B causes A. Both may result from some unevaluated cause C.
Science is not description, it is explanation. The linked article describes, and then draws a conclusion that goes far beyond the description. But it never presumes to explain why the author's conclusion might be so.
> "A predicts B" does NOT AT ALL imply "A causes B"
It certainly does. Rain predicts puddles. Puddles do not predict rain, they follow from it.
You're missing the crucial distinction between describing and explaining. A correlation is a description, and descriptions aren't science. Only by proposing an explanation, then testing it, do we enter the domain of science. We also have the chance to turn a correlation into something more than a coincidence.
If you want to separately discuss the former, I don't have a strong opinion about it any which way. We do need to document correlations somewhere, because 1) they are a useful starting point when looking for causal relationships, and 2) we might be able to make use of them before we understand why they work. We do need some quality controls to ensure that we are finding correlations that really exist, and I don't see a problem with using the infrastructure around "properly" scientific experiment to this end, but if you propose we move it somewhere else or simply call it something else I don't see any big problems with that.
This is a science magazine, the reporter would have read a lot of papers over his career, and because "A predicts B" is such a common use to denote correlation in statistics, I wouldn't blame him/her.
Guys like Hafiz and Hemingway were both alcoholics by today's standards, and thank God for that and for their creativity
False! Creativity is correlated with a longer life.
> A large body of research links neuroticism with poorer health and conscientiousness with superior health. [Emphasis added.]
There's that word again -- "links". Neuroticism is not linked with poorer health, it is correlated with poorer health.
And so forth -- frankly, the linked article is a piece of pseudoscientific trash.
Psychologists would be so much happier if there simply wasn't any science at all, rather than the kind they practice -- the kind that avoids control groups, experimental discipline, can't seem to express correlations accurately, and draw nonsense conclusions like this:
"...the results suggest that practicing creative-thinking techniques could improve anyone's health by lowering stress and exercising the brain."
Without a control group, without a disciplined, prospective, double-blind, replicated study, the "results" suggest no such thing. Isn't obvious that creative thinking may be an effect, not a cause, of good physical and mental health?
Reading articles like this, I begin to suspect that in school, psychologists are told, "say the word 'science' a lot -- that's how you do science."
Having creativity is highly correlated with a longer life, therefore, creativity can be used as a factor to predict whether a person has longer life.
It doesn't mean that if you get more creative you live longer, just that if you look at the existing population, the more creative people are likely to live longer also.
See?
Search for this phrase in this paper "We show how simple image statistics can be used to predict the presence and absence of objects in the scene before exploring the image."
http://cvcl.mit.edu/papers/TorralbaOliva03.pdf
You can see how "predict" is a word for an action you can take if something is correlated.
This is false. I saw a puddle, so I predict that the puddle will cause rain. See the problem? You can't "predict" until you have a cause-effect relationship.
A correlation is not a cause-effect relationship:
http://en.wikipedia.org/wiki/Correlation_does_not_imply_caus...
A quote: "The opposite belief, correlation proves causation, is a logical fallacy by which two events that occur together are claimed to have a cause-and-effect relationship. The fallacy is also known as cum hoc ergo propter hoc (Latin for "with this, therefore because of this") and false cause. It is a common fallacy in which it is assumed that, because two things or events occur together, one must be the cause of the other."
> You can see how "predict" is a word for an action you can take if something is correlated.
You may be able to do that. Scientists require evidence.
[1] If the weather in the area tends to be the same day to day, then I can absolutely predict rain tomorrow based on puddles today, to occasionally be frustrated by weather change or sprinklers.
I am not confused. Confusing correlation with causation is a very common logical error -- you are not alone.
That might be true if anyone had said it (avoid rhetorical escalation).
> And yes, confusing correlation with causation is a common logical error - one that, I believe, you have become oversensitive to such that you are spotting it where it doesn't exist.
The post that started this thread correctly identifies a case of touting a correlation as though it represents a cause-effect relationship. This is very common in popular science journalism, where data sets that barely represent a correlation are described as though they were cause-effect relationships, and begin to shape public policy well in advance of, and sometimes in the perpetual absence of, any effort to establish a cause-effect link between some A and some B.
You have a habit of denying the obvious that is leading me to believe you are trolling, your profile and post history to the contrary.
You said, word for word, "I am not confused."
You then proceeded to say, "Confusing correlation with causation is a very common logical error -- you are not alone." This is quite clearly a statement that I am confused about correlation vs. causation.
Therefore, semantically, you said "I am not confused, you are" plus the well established point that confusion was related to correlation and causation.
You broke your own example by inserting the word "cause" into the sentence. Of course your example is a cause-effect relationship.
Statistical evidence suggesting correlation of two factors A and B are enough for one to say "The presence of A predicts B" as well as "The presence of B predicts A".
Please, don't warp the meaning of the word "predict".
"I predict tomorrow is going to rain" There is no way that sentence suggests a cause-effect relationship.
"This specific color pattern in the image is a great predictor of the presence of rain when the photograph was taken" Neither does this sentence suggests a cause-effect relationship.
No one here is confused between correlation and causation. I'm simply insisting the word "predict" has to do with correlation, not causation.
Yes -- evidence of a correlation, not a cause-effect relationship.
> Of course your example is a cause-effect relationship.
Puddles and rain? Yes, but it is only a description, not an explanation. Science requires explanations. Otherwise we open the door to pseudoscience, to people claiming any associations they care to claim.
> Please, don't warp the meaning of the word "predict".
It is you who is doing that -- look at the definitions at the bottom of this post.
Here's another example. I have a cure for the common cold -- I shake a dried gourd over the patient's head until he get better. Sometimes it takes a week, but my treatment always works. The correlation is perfect, therefore I deserve a Nobel Prize for ridding the world of this scourge.
My dried gourd treatment "predicts" that the cold sufferer will get better -- always.
> I'm simply insisting the word "predict" has to do with correlation, not causation.
And you are mistaken. Rain is a predictor for bumper crops, but bumper crops are not a predictor for rain. Teenage driving is a predictor for car crashes, but car crashes are not a predictor for teenage driving.
A recent bogus study found a correlation between marijuana use and lower IQ. But the marijuana use did not predict the IQ drop, it was only correlated with it, and the researchers included this fact in their article. Needless to say, the science journalists ignored the qualifiers in the article and announced that marijuana use predicted a fall in IQ:
http://abcnews.go.com/blogs/health/2012/08/27/teenage-mariju...
Here's another account of the same study that makes a claim in its title that the article body contradicts. Title: "Smoking Pot In Teen Years Lowers IQ Later". A quote from the article: "But those who consistently smoke marijuana may simply make less intellectually stimulating choices at critical points in life."
Here is another bogus study: "Low I.Q. Predicts Heart Disease":
http://well.blogs.nytimes.com/2010/02/10/low-i-q-predicts-he...
Except for the fact that it's only a correlation, and use of the term "predicts" is nonsense. Needless to say, the article doesn't consider that the low IQ might predict the heart disease, not the reverse.
> I'm simply insisting the word "predict" has to do with correlation, not causation.
Yes, and you are mistaken.
http://dictionary.reference.com/browse/predict
"to declare or tell in advance; prophesy; foretell: to predict the weather; to predict the fall of a civilization."
http://www.merriam-webster.com/dictionary/predict
"to declare or indicate in advance; especially : foretell on the basis of observation, experience, or scientific reason"
Q.E.D.
I meant to say your example of course implied a cause-effect relationship, since you added the word 'cause' to it. (of course it wasn't a cause-effect relationship, do you think I am stupid?)
>> My dried gourd treatment "predicts" that the cold sufferer will get better -- always.
If your treatment is indeed correlated with a cold sufferer getting better, significantly enough, then yes, your treatment does in fact predicts it, even though it might not have been the cure. This is consistent with the definition of prediction being only related to correlation.
>> Rain is a predictor for bumper crops, but bumper crops are not a predictor for rain. Teenage driving is a predictor for car crashes, but car crashes are not a predictor for teenage driving.
That is correct; since bumper crops were only aided by rain if factors X1, Y1 are true, bumper crops are not a predictor of past rain unless X1, Y1 is true. Car crashes are correlated with teenage driving if factors X2, Y2 are true, car crashes are not a predictor of teenage driving unless X2, Y2 is true.
X1, Y1 = (Crops are water dependent, crops were not also thoroughly irrigated by other means)
X2, Y2 = (Teenager was intoxicated, teenager riding in car with more than 3 other members, all male)
>> But the marijuana use did not predict the IQ drop, it was only correlated with it, and the researchers included this fact in their article.
Yes it did, correlation means you can use the statistics to predict it, even if it wasn't the cause.
Predict means correlation, and correlation means what you think correlation means. You have the meaning of predict wrong. It has as much to do with causation as correlation has. i.e not much (though some nonetheless, since if there is a causation it is likely to be correlated).
"In statistics, prediction is a part of statistical inference. One particular approach to such inference is known as predictive inference, but the prediction can be undertaken within any of the several approaches to statistical inference. Indeed, one description of statistics is that it provides a means of transferring knowledge about a sample of a population to the whole population, and to other related populations, which is not the same as prediction over time."
http://en.wikipedia.org/wiki/Prediction#Statistics
If you are talking about prediction and correlation in the same sentence, you are in the realm statistics and therefore should abide by its use of language.
You also did not address my two examples of use of predict in laymen sentences showing the word "predict" did not have anything to do with causation.
>> "to declare or tell in advance; prophesy; foretell: to predict the weather; to predict the fall of a civilization."
>> "to declare or indicate in advance; especially : foretell on the basis of observation, experience, or scientific reason"
Neither of those definitions have any semblance of implying causation. Observation, experience, or scientific reason can all be instances of correlation.
Of course I can. I chose only those points where your logical errors were most obvious.
> If your treatment is indeed correlated with a cold sufferer getting better, significantly enough, then yes, your treatment does in fact predicts it, even though it might not have been the cure. This is consistent with the definition of prediction being only related to correlation.
No, that is false. Shall I list the definitions for "predict" again, or will you read them again on your own?
> You also did not address my two examples of use of predict in laymen sentences showing the word "predict" did not have anything to do with causation.
You quoted some laymen who suited your purpose, while I listed the dictionary definitions for the word, the definitions that show that "predict" means to assert an effect based on a cause.
> Neither of those definitions have any semblance of implying causation.
Oh, really?
"to declare or indicate in advance; especially : foretell on the basis of observation, experience, or scientific reason"
A prediction is therefore the use of observations of A to predict B, to show a cause-effect relationship. I see the disappearance of the middle class (A), and on that basis I predict the fall of civilization (B). I see gathering clouds (A), and on that basis I predict rain (B) -- and puddles (C).
> Observation, experience, or scientific reason can all be instances of correlation.
Yes, but it's a false analogy with no bearing on this topic. A prediction forges a link between an observation (A) and an outcome (B). It assumes a cause-effect relationship, one that may not be real, but a word isn't responsible for how people misuse it.
> Indeed, one description of statistics is that it provides a means of transferring knowledge about a sample of a population to the whole population
Yes -- an observation of a small sample (A) is used as the basis for a prediction about the population as a whole (B). Also, remember that "prediction" commonly refers to an assertion about the future (B) based on present observations (A).
http://dictionary.reference.com/browse/predict
"(Verb) to foretell the future; make a prediction."
> Yes it did, correlation means you can use the statistics to predict it, even if it wasn't the cause.
Nonsense. Marijuana use doesn't predict an IQ drop, the study doesn't support that prediction, as the authors were careful to point out, and as the journalists were at pains to ignore.
The marijuana use, and the IQ drop, are only correlated -- one does not predict the other.
You are using the temporal sense of the word "predict", not the cross-sectional sense. Just because you can use the word predict when there is a cause-effect relationship doesn't mean you can't if there isn't. Here is an example illustrating this: I see lots of graffiti in the town (A) and on that basis, predict this town has a high crime rate (B). Notice this prediction was made independent of time.
>> A prediction forges a link between an observation (A) and an outcome (B). It assumes a cause-effect relationship, one that may not be real, but a word isn't responsible for how people misuse it.
A prediction forges a link between an observation (A) and an outcome (B) to explain a correlation relationship, which may or may not be because of a cause-effect relationship.
>> Yes -- an observation of a small sample (A) is used as the basis for a prediction about the population as a whole (B). Also, remember that "prediction" commonly refers to an assertion about the future (B) based on present observations (A).
Let's say I am a statistician and after surveying 10% of the population, found out lower income earners are correlated with a lower IQ. I use this observation as a basis for a prediction about the population as a whole - that lower income earners can predict a lower IQ. Notice again, time is irrelevant.
>> Also, remember that "prediction" commonly refers to an assertion about the future (B) based on present observations (A).
A word may have more than one sense. I am talking about the word prediction as used in statistics.
>> The marijuana use, and the IQ drop, are only correlated -- one does not predict the other.
If they are correlated then you can use the evidence in the sample to make general predictions in the population (independent of time), provided your experiment methodology was valid.
Yes -- that's because that's how the word is defined.
http://en.wikipedia.org/wiki/Prediction
"A prediction (Latin præ-, "before," and dicere, "to say") or forecast is a statement about the way things will happen in the future, often but not always based on experience or knowledge." (Emphasis added.)
> A word may have more than one sense. I am talking about the word prediction as used in statistics.
Yes, all right. Statistics uses the word in the same way, for the same purpose -- as a description of a forecasting method, a statement about the future based on past and present data. Consider the various regression-based prediction methods that are, by definition, statements about the future, based on the past.
http://www.isixsigma.com/tools-templates/risk-management/use...
"Forecasting is a business and communicative process and not merely a statistical tool. Basic forecasting methods serve to predict future events and conditions and should be key decision-making elements for management in service organizations."
Shall I list ten more references that make the same point about statistical prediction? How about just one:
http://en.wikipedia.org/wiki/Regression_analysis
"Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning."
> If they are correlated then you can use the evidence in the sample to make general predictions in the population ...
Only if you don't understand science. Correlation is not causation.
Regression is for predicting a dependent variable based one or more independent variables. It may or may not involve a time component.
"Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning."
Exactly. Prediction and forecasting are not the same thing. That's why they had to state both.
I know your bio is impressive, but I've studied statistics for two years, specifically time-series forecasting and regression modelling. Predictions are a lot of the times not made in a temporal context. E.g. if you predict aspects of the population based on your observations in a sample.
>> Only if you don't understand science. Correlation is not causation.
I might not understand science as well as you do, but I have some modicum of ability in statistics, so there's no need to wave "Correlation is not causation." at me in every reply you make.
Prediction are not always made as a result of a causation.
"Prediction" and "forecasting" are synonymous, in both common usage and in statistics.
> Prediction and forecasting are not the same thing. That's why they had to state both.
No they said both so people who refuse to accept the fact that they're synonymous, won't feel left out in the cold.
http://en.wikipedia.org/wiki/Prediction : "A prediction (Latin præ-, "before," and dicere, "to say") or forecast is ..."
http://en.wikipedia.org/wiki/Forecasting : "Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term."
http://dictionary.reference.com/browse/prediction: "Synonyms: forecast, augury, prognostication, divination, projection."
http://dictionary.reference.com/browse/forecast: "Synonyms: 1. foretell, anticipate. See predict. 3. project. 4, 7. guess, estimate. 9. forethought, prescience."
How can you go on like this about a word that literally means "to say before"?
> Predictions are a lot of the times not made in a temporal context ...
Yes, but those also represent the use of a set of observations (A) to assert a cause-effect relationship with some B. You objected that "prediction" wasn't about time, but it is. You also objected that prediction wasn't about arguing a cause-effect relationship, but it is.
> Prediction are not always made as a result of a causation.
Yes, and "literally" doesn't always mean literally -- sometimes it means "figuratively.":
http://dictionary.reference.com/browse/literally:
"1. in the literal or strict sense: What does the word mean literally?
4. in effect; in substance; very nearly; virtually."
The above is my favorite example of the perversity of arguing about word meanings, as though a word that usually means something, can be said to always mean that.
> I know your bio is impressive ...
Oh, please, let's not go there, all right? Nothing is more certain to undermine an argument than an appeal to authority -- either positive of negative (an in "I'm not an authority, but ..."). Science rejects authority -- the largest amount of eminence is trumped by the smallest amount of evidence.
http://en.wikipedia.org/wiki/Prediction#Statistics
It's not forecasting if it doesn't involve time, but it is if it does. That's why you can find evidence saying "Prediction == Forecasting" because that is true if there is a time component.