Applying a filter to a data stream will remove noise and make a graph of the data easier to read and interpret. Most software packages provide a filter for each channel, and the user can select how much to filter, or smooth, each trace. The sample rate at which a particular channel is set can also be used to filter the data. For example, a channel that does not change quickly, such as speed, can be sampled at a slow rate that will naturally smooth out most noise. Other channels may need to be sampled at a higher rate and then filtered to avoid losing data.
In general, set the sampling rate for a given channel no higher than necessary. Not only will this avoid unwanted noise on the channel, it will also reduce the memory requirements and file sizes you’ll have to deal with. Look at each channel unfiltered, and add only enough filter or smoothing so that noise on the trace is smoothed out but the data trace itself is unaffected. The attached examples clearly show the effects of not enough and too much smoothing.