Run chart
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Run chart 1 Run chart A simple run chart showing data collected over time. The median of the observed data (73) is also shown on the chart. A run chart, also known as a run-sequence plot is a graph that displays observed data in a time sequence. Often, the data displayed represent some aspect of the output or performance of a manufacturing or other business process. Overview Run sequence plots [1] are an easy way to graphically summarize an univariate data set. A common assumption of univariate data 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 the current position on the line (vertical axis) versus the time steps (horizontal axis). Examples could include measurements of the fill level of bottles filled at a bottling plant or the water temperature of a dishwashing 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] Run charts are similar in some regards to the control charts used in statistical process control, but do not show the control limits of the process. They are therefore simpler to produce, but do not allow for the full range of analytic techniques supported by control charts.
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Software Quality ManagementAnna University SyllabusB.E. IV CSEAbout Run Chart
Transcript of Run chart
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/
