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The correlation of data is a measure of how much one variable is affected by another. Thus, if for a given variable x the variable y can be predicted in some sort of straight line relationship, then they may be said to be correlated.

For normally distributed data Pearson's correlation coefficient, r, is used, which has a value of -1 to 1. Zero implies no correlation; a negative number implies that increasing x decreases y. The closer to 1 (or -1) the better the correlation.

Note that for a given line equation, y=mx + c, where m is the gradient, and c the y axis intercept, the correlation coefficent is not the same as the gradient.

For data that is not normally distributed Spearmans or Kendalls correlations are used.


General Practice Notebook
General Practice Notebook
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