A simple method for smoothing noisy data is to use a moving average. The original data is partitioned into overlapping sets of a given sample size, typically by shifting along one step at a time. The new smoothed data is made by computing the average for each of the sets. Larger sample sizes result in greater smoothing. Using the median of the sample sets gives a moving median for the data and produces different smoothing effects.