Correlation can only show that one variable increases linearly as another increases or decreases. It cannot show non-linear relationships. There can, therefore, be a perfect non-linear relationship and the correlation coefficient can be zero. For example y = x2 in the range (-a, a) for any positive number a,
Second, correlation cannot determine whether A causes B or B causes A. There is probably a good correlation between my age over the last 10 years and the number of white hairs on my head. However, I do not think that white hairs caused me to GROW older (I may look older, but that is another matter entirely).
Furthermore, when there are two correlated variable, there may not be any causal relationship between the two variables but there may be a third variable that causes both. There is a fairly good correlation between my age and the number of cars in the UK. My growing old did not increase the number of cars and the number of cars did not make me grow old. So there is no causal relation between them. Instead, both are correlated to time.
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A positive correlation between two variables, say X and Y, means that if one increases, the other will too. No correlation means that they are not related. A negative correlation means that as one increases, the other decreases. Normally you will see this in studies as "Recent studies demonstrated a positive correlation between eating too much and obesity." Or, "recent studies demonstrate a negative correlation between a healthy, balanced diet and obesity".
Yes it depends on what you are measuring in your study. some examples of variable include age, sex, marital status among others
Acountance
People say (and studies show) that this ratio is aesthetically pleasing. Of any rectangle, people like the golden rectangle the most. However, even though studies show a correlation between the ratio phi and beauty, it is important to know that these studies do not imply causation. Artists like to use it because the ratio is aesthetically pleasing, but I believe it has more to do with muscles in the eye and their movements being easier to encompass the whole picture than any of this golden ratio stuff.
A statistician