A correlation is the strength and direction of the relationship between two variables.^{[1]} A correlation is measured with a correlation coefficient. A correlation coefficient of 1 means the variables are perfectly related to each other in a positive manner (y ≈ ax + b, a > 0). A correlation coefficient of 0 means the variables are not related to each other (y ≠ x). A correlation coefficient of -1 means the variables are perfectly related to each in a negative manner (y ≈ ax + b, a < 0).
Correlation can be considered the amount of 'noise' in a dataset. This noise can be measurement error or complicating factors.
Figure 1: Several sets of (x, y) points, with the correlation coefficient of x and y for each set. |
# | A | B | C | D |
E | F | G | H | I |
J | K | L | M | N |
O | P | Q | R | S |
T | U | V | W | Y |
Z | X |
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