Linear or straight line graphs are commonly used during the analysis of experimental data to represent relationships between real life variables. One reason for this is that experimental measurements often contain a lot of 'noise', due to unknown factors, so it would not be sensible to use complicated curves to represent relationships when the data itself is imprecise. Another reason is that linear graphs have important and well understood characteristics.

This section examines the important features of linear graphs.

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