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Measuring Correlation

In the previous section, you used words such as strong, weak, positive, and negative to describe correlation.
However, there is also a numerical value that describes the strength and sign of the correlation.

It is called the Pearson's product-moment and is usually denoted with the letter .


In the Desmos window above, the value of $\text{corr}\left(x_1,y_1\right)$ is the value of $r$.

When there is perfect positive correlation between two variables, $r=$
Drag the data points so that they form a descending line.

When there is perfect negative correlation between two variables, $r=$
Drag the data points so that they are scattered with no apparent trend.

When there appears to be no correlation between two variables, the value of $r$ is close to

Here are some other values of $r$ and their scatter diagrams.

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$r=0.9$
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$r=0.4$
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$r=-0.3$
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$r=-0.65$

When $r=0.9$, there is a linear correlation between the two variables.
When $r=0.4$, there is a linear correlation between the two variables.
When $r=-0.3$, there is a linear correlation between the two variables.
When $r=-0.65$, there is a linear correlation between the two variables.
This table summarizes how the value of $r$ describes the correlation.
Pearson's correlation
coefficient ($r$)
Correlation
$0 \le r \le 0.25\qquad$ no / very weak
$0.25 \lt r \le 0.5\phantom{0}\qquad$ weak
$0.5 \lt r \le 0.75\qquad$ moderate
$0.75 \lt r \lt 1\phantom{.00}\qquad$ strong
$r = 1\phantom{.00}\qquad$