Run charts (often known as line graphs outside the quality management field) display process performance over time. Upward and downward trends, cycles, and large aberrations may be spotted and investigated further. In a run chart, events, shown on the y axis, are graphed against a time period on the x axis. For example, a run chart in a hospital might plot the number of patient transfer delays against the time of day or day of the week. The results might show that there are more delays at noon than at 3 p.m. Investigating this phenomenon could unearth potential for improvement. Run charts can also be used to track improvements that have been put into place, checking to determine their success. Also, an average line can be added to a run chart to clarify movement of the data away from the average.
Both of these mistakes are common, but people are generally less aware that they are making the first type, and are tampering with a process which is really behaving normally. To avoid mistakes, use the following rules of thumb for run chart interpretation:
If you have 25 points or more in your data series, you can use run charts to detect special causes - something beyond the usual variability of the process -acting on the process.
For more robust monitoring of a process, and better information about when your process is showing variation beyond what is expected, try using a control chart. It will detect special causes more quickly, and with more accuracy.
For each line in the run chart, the following statistics are calculated:
|Mean||the average of all the data points in the series.|
|Maximum||the maximum value in the series.|
|Minimum||the minimum value in the series.|
|Sample Size||the number of values in the series.|
|Range||the maximum value minus the minimum value.|
|Standard Deviation||Indicates how widely data is spread around the mean|