It is a measure of the extent to which a linear change in one quantity is accompanied by a linear change in the other quantity. Note that only linear changes are measured and that there is no causality.
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It means that there is a general tendency that, if one quantity increases, the other also increases (positive correlation) or decreases (negative correlation). The correlation coefficient is the result of a formula, and tells you how strong the dependency is. For example, a correlation close to zero means that there is no correlation; that any variations in the second variable seem to be random.
There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.
Correlation is a statistical measure of the linear association between two variables. It is important to remember that correlation does not mean causation and also that the absence of correlation does not mean the two variables are unrelated.
A ratio is a comparison of two quantities
A scatterplot is the best tool. Regression or correlation can often fail to find non-linear relationships.
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".