Run chart 1

Run chart

A simple run chart showing data collected over time. The median of the observeddata (73) is also shown on the chart.

A run chart, also known as a run-sequenceplot is a graph that displays observed data ina time sequence. Often, the data displayedrepresent some aspect of the output orperformance of a manufacturing or otherbusiness process.

Overview

Run sequence plots[1] are an easy way tographically summarize an univariate dataset. A common assumption of univariatedata sets is that they behave like:[2]

• random drawings;• from a fixed distribution;• with a common location; and• with a common scale.With run sequence plots, shifts in location and scale are typically quite evident. Also, outliers can easily be detected.

Run chart of eight random walks in one dimension starting at 0. The plot shows thecurrent position on the line (vertical axis) versus the time steps (horizontal axis).

Examples could include measurements ofthe fill level of bottles filled at a bottlingplant or the water temperature of adishwashing machine each time it is run.Time is generally represented on thehorizontal (x) axis and the property underobservation on the vertical (y) axis. Often,some measure of central tendency (mean ormedian) of the data is indicated by ahorizontal reference line.Run charts are analyzed to find anomalies indata that suggest shifts in a process overtime or special factors that may beinfluencing the variability of a process.Typical factors considered include unusuallylong "runs" of data points above or belowthe average line, the total number of such runs in the data set, and unusually long series of consecutive increases ordecreases.[1]

Run charts are similar in some regards to the control charts used in statistical process control, but do not show thecontrol limits of the process. They are therefore simpler to produce, but do not allow for the full range of analytictechniques supported by control charts.

Run chart 2

References  This article incorporates public domain material from websites or documents [3] of the National Institute of

Standards and Technology.[1] Chambers, John; William Cleveland, Beat Kleiner, nd Paul Tukey (1983). Graphical Methods for Data Analysis. Duxbury.

ISBN 053498052X.[2] NIST/SEMATECH (2003). "Run-Sequence Plot" (http:/ / www. itl. nist. gov/ div898/ handbook/ eda/ section3/ runseqpl. htm) In:

e-Handbook of Statistical Methods 6/01/2003 (Date created).[3] http:/ / www. nist. gov

Further reading• Pyzdek, Thomas (2003). Quality Engineering Handbook (Second Edition ed.). New York: CRC.

ISBN 0-8247-4614-7.

External links• Run-Sequence Plot (http:/ / www. itl. nist. gov/ div898/ handbook/ eda/ section3/ eda33p. htm)

Article Sources and Contributors 3

Article Sources and ContributorsRun chart  Source: http://en.wikipedia.org/w/index.php?oldid=402132258  Contributors: Btyner, Craigkbryant, DanielPenfield, David Haslam, Davidelit, G716, Hooperbloob, Linas, Mdd,Melcombe, Michael Hardy, Nekohakase, Paul August, Pmc, Qwfp, 10 anonymous edits

Image Sources, Licenses and ContributorsImage:SimpleRunChart.jpg  Source: http://en.wikipedia.org/w/index.php?title=File:SimpleRunChart.jpg  License: Public Domain  Contributors: MddImage:Random Walk example.png  Source: http://en.wikipedia.org/w/index.php?title=File:Random_Walk_example.png  License: GNU Free Documentation License  Contributors: ChongDae,Darapti, Mdd, Ordoon, Toobaz, 1 anonymous editsImage:PD-icon.svg  Source: http://en.wikipedia.org/w/index.php?title=File:PD-icon.svg  License: Public Domain  Contributors: User:Duesentrieb, User:Rfl

LicenseCreative Commons Attribution-Share Alike 3.0 Unportedhttp:/ / creativecommons. org/ licenses/ by-sa/ 3. 0/