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 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 in example of a positive correlation between high school and university exam results above might suggest a causation, there are 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.



Australian Bureau of Statistics - Correlation and Causation: this overview  of correlation and causation is easy to follow and explains the major features of correlation and its difference from causation.

Interpreting Correlations: An interactive visualization: this tool allows users to gain an understanding of negative and positive correlations though the use of an interactive scatter plot representing the user-controlled strength and polarity of a correlation value.


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


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Updated: 19th August 2014 - 11:29am
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BetterEvaluation Knowledge Platform Manager, BetterEvaluation.
Melbourne, Australia.


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