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# Data with two variables

### Measuring the variability

With single variable data we calculated the measure of spread to quantify the variability in the data set (e.g. standard deviation).

• The strength of the linear relationship between two variables is called the correlation coefficient ($$r$$).
• You can calculate the correlation coefficient on most scientific calculators.
• The correlation coefficient is a value that can only be between $$−1$$ and $$1$$.
• The closer the correlation coefficient is to either $$-1$$ or $$1$$, the stronger the linear correlation will be.
• A negative correlation coefficient means that the relationship is negative (as $$x$$ increases, $$y$$ decreases). A positive correlation coefficient means that the relationship is positive (as $$x$$ increases, $$y$$ increases).
• For example the correlation coefficient is $$r \approx 0.966$$.
• This implies a strong positive relationship between the two variables. To note: the presence of a strong linear correlation does not imply a cause/effect relationship.