Correlation is NOT causation. Tony's right and like I said before, you're a retard.
Causality, at least the type you're referring to, requires 3 factors -
A statistically sig. relationship
The causal variable must precede the other variable
No other factors can account for the cause
With intelligence and education, you fail miserably in the second 2. Intelligence may very well precede education. And other factors such as testing ability and aptitude, type of measurements, etc., socioeconomic issues, and any number of issues may all contribute to the cause.
Sadly, this is statistics 101 - and you fail...as usual.
Here's a novel idea - post your proof moron.
i agree meatpie, nothing of what i said contradicts what you said. Jesus, go to a statistic class
here learn something other then basic statistics you twit
http://en.wikipedia.org/wiki/Linear_regressioni guess the famous geneticist and mathmetician i quoted failed stats 101.
again much more elequently then i have stated
'Causation' has been popularly used to express the condition of association, when applied to natural phenomena. There is no philosophical basis for giving it a wider meaning than partial or absolute association. In no case has it been proved that there is an inherent necessity in the laws of nature. Causation is correlation... [P]erfect correlation, when based upon sufficient experience, is causation in the scientific sense.
— Henry E. Niles
a significant relationship refers to the t score exceeding a p level, usually 5% in academia, this leaves a 5% chance your results are not due to the independent variable but insted chance, or some extraneous nuisance variable. WRT to no other factors, chance even in significant results do exist, this can be lowered with increased power of an experiement or more stringent alpha level, in fact sometimes changing from a .05 to .01 actually makes the results non-significant, thus wrecking the supposed causality and significant relationship.
I don't know how to explain it any further to you, its obvious neither of you have a rudimentary understanding of stats, as you have said nothing actually involving statistics, while i have given various examples only to be ignored.
again correlation is a continuim. At zero there is no correlation and the two variables x and y do not share a relationship. As you increase the correlation the likelihood of chance decreases and the variables have a stronger predicitive relationship. At 95-995 confidence interval we usually conclude causality, this is arbitrary, obviously however it is universally agreed upon. All degrees of CORRELATION ARE NOT CAUSATIVE BUT COULD BE, HOWEVER, THEY ARE INCREASINGLY UNLIKELY DUE TO HIGHER PROBABILITY OF EXTRANEOUS VARIABLES AND CHANCE, AT 95% CONFIDENCE INTERVAL WE SAY ITS CAUSATIVE, WITH A 5% CHANCE OF THE RESULTS OR THE INDEPENDENT VARIABLE NOT ACCOUNTING FOR THE DEPENDENT VARIABLE.
white is all the colors of the spectrum, blue is a seperate color but white contains blue but also other spectrums. This analogy aids us in correlation as correlation contains none to perfect, with perfect being causation, however, not all of correlation is causation, it is a part of it however. as an aside, causation is arbitrarty.
still dont get what im saying, then i cant help you. im under the impression you dont know what causation nor correlation actually is. in the example of education if there is a 75% chance or correlation with intelligence we run a mulitple regression analysis to account for other correlative variables. We apply a particular alpha level and weight to those, we can then conclude if the variable is likely causative if the value for it obtained falls within a pre-determined confidence interval
http://en.wikipedia.org/wiki/Confidence_intervalor use bayesian methods.
http://en.wikipedia.org/wiki/Analysis_of_variance multiple means
you also should split intelligence up and say that increased or improved intelligence correlates with education success, however, the construct of intelligence is not a concrete thing but a fluid abstact thing, thus its unlikely there is a causative factor or a single causative factor, however, clusters can be causative.
owned much?