Correlation is ​a statistical measure ranging from +1.0 to -1.0, represented by 'r', that indicates how strongly two or more variables are related and whether that relationship is positive or negative.

A positive correlation (+1.0 to 0) indicates that the two variables move in the same direction, e.g., the variable of high school exam results might have a positive correlation with the variable of university exam results. A positive correlation of 0.97 is shown below: Graphic created with Interpreting Correlations tool (Magnusson, n.d.).

A negative correlation (0 to -1.0) indicates that the variables move in opposite directions, e.g., years spent driving might have a negative correlation with the amount of driving accidents. A negative correlation of -0.97 is shown below: Graphic created with Interpreting Correlations tool (Magnusson, n.d.).

The strength of a correlation (how closely the two variables are linked) is indicated by the value of 'r'. If 'r' is +1 or -1, very is a very strong correlation. If 'r' is 0, there is no correlation: Graphic created with Interpreting Correlations tool (Magnusson, n.d.).

It's important to note that correlation does not equal causation. While an example of a positive correlation between high school and university exam results above might suggest causation, there is a range of factors that need to be addressed. For example, hours spent studying, family background, life goals, amount of time spent socializing, or intellect might all play a part in causing the correlation.

Correlation can show the strength and direction of a relationship between variables. But it's up to controlled experiments and well-designed research studies to show causation.

## Sources

Magnusson, K. (n.d.). 'Interpreting Correlations: an interactive visualization' [webpage]. Retrieved from https://rpsychologist.com/correlation/