Time series plots are often ‘noisy’, with many random fluctuations that make it difficult to analyse the long-term pattern of the data.

Numerical smoothing provides a method of lessening the impact of those random fluctuations so that the pattern is easier to discern.

The two methods for numerical smoothing used in further maths are moving mean and moving median smoothing.

In both methods, a new set of values are created by taking a group of data points, finding the mean or median, then moving to the next group (by replacing the first data point in the group with the next data point not yet included).