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It is important to be able to identify relationships in data. This allows trends to be recognised and may allow for predictions to be made. Relationships in data can be identified in several ways.

Scatter graphs

These graphs show the relationship between two sets of data, eg number of tourists and number of tourist facilities or weight and height.

A line of best fit helps to show correlations, or patterns within the data. The line of best fit runs through the middle of points on the graph, ideally with an equal number of points on either side of the line.

• A strong correlation is when the points are very close to the line of best fit.
• A weak correlation is when the points are far away from the line of best fit.
• A positive correlation is when an increase in one factor is mirrored by an increase in another (the line of best fit goes from the bottom left to the top right).
• A negative correlation is when an increase in one factor is mirrored by a decrease in another (the line of best fit goes from the top left to the bottom right).

Interpolate trends

This is when a value is found within the data set, using the line of best fit. The value was not originally plotted, but can be read off the line of best fit.

Extrapolate trends

This is when a value is found outside of the data set. Extrapolation may provide uncertain results as it is based on extending the line of best fit beyond a known set of data.