With run sequence plots, shifts in location and scale are typically quite evident. Also, outliers can easily be detected.
Examples could include measurements of the fill level of bottles filled at a bottling plant or the water temperature of a dish-washing machine each time it is run. Time is generally represented on the horizontal (x) axis and the property under observation on the vertical (y) axis. Often, some measure of central tendency (mean or median) of the data is indicated by a horizontal reference line.
Run charts are analyzed to find anomalies in data that suggest shifts in a process over time or special factors that may be influencing the variability of a process. Typical factors considered include unusually long "runs" of data points above or below the average line, the total number of such runs in the data set, and unusually long series of consecutive increases or decreases.[1]
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