A measure of the degree of interrelationship which exists between two measured quantities, $x$ and $y$; the correlation coefficient ($r$) is defined by the following relation: $$r=\frac{\sum _{\begin{array}{c}i=1\end{array}}^n(x_i-\bar{x})(y_i-\bar{y})}{\sqrt{\sum _{\begin{array}{c}i=1\end{array}}^n(x_i-\bar{x}{)}^2\sum _{\begin{array}{c}i=1\end{array}}^n(y_i-\bar{y}{)}^2}}$$ where $x_i$ and $y_i$ are the measured values in the $i$th experiment of $n$ total experiments, $\bar{x}$ and $\bar{y}$ are the arithmetic means of $x_i$ and $y_i$: $$\bar{x}=\frac{\sum _{\begin{array}{c}i=1\end{array}}^n{x}_i}{n}$$ (similar expression for $\bar{y}$). The linear correlation coefficient indicates the degree to which two quantities are linearly related. If $x=ay$ is followed then $r=1$, and departures from this relationship decrease $r$; if interpretations of data based on the linear correlation coefficient are to be made, one should consult a book on statistics.