Plot (graphics)

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Scatterplot of the eruption interval for Old Faithful (a geyser).

A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables. The plot can be drawn by hand or by a mechanical or electronic plotter. Graphs are a visual representation of the relationship between variables, very useful for humans who can quickly derive an understanding which would not come from lists of values. Graphs can also be used to read off the value of an unknown variable plotted as a function of a known one. Graphs of functions are used in mathematics, sciences, engineering, technology, finance, and other areas.

Overview[edit]

Plots play an important role in statistics and data analysis. The procedures here can broadly be split into two parts: quantitative and graphical. Quantitative techniques are the set of statistical procedures that yield numeric or tabular output. Examples of quantitative techniques include:[1]

These and similar techniques are all valuable and are mainstream in terms of classical analysis. There are also many statistical tools generally referred to as graphical techniques. These include:[1]

Graphical procedures such as plots are a short path to gaining insight into a data set in terms of testing assumptions, model selection, model validation, estimator selection, relationship identification, factor effect determination, outlier detection. Statistical graphics give insight into aspects of the underlying structure of the data.[1]

Graphs can also be used to solve some mathematical equations, typically by finding where two plots intersect.

Types of plots[edit]

\vec{x}(i)\approx \vec{x}(j),\,
showing i on a horizontal axis and j on a vertical axis, where \vec{x} is a phase space trajectory.

Examples[edit]

Types of graphs and their uses vary very widely. A few typical examples are:

See also[edit]

References[edit]

 This article incorporates public domain material from websites or documents of the National Institute of Standards and Technology.

  1. ^ a b c NIST/SEMATECH (2003). "The Role of Graphics". In: e-Handbook of Statistical Methods 6/01/2003 (Date created).
  2. ^ Altman DG, Bland JM (1983). "Measurement in medicine: the analysis of method comparison studies". The Statistician (Blackwell Publishing) 32 (3): 307–317. doi:10.2307/2987937. JSTOR 2987937. 
  3. ^ Bland JM, Altman DG (1986). "Statistical methods for assessing agreement between two methods of clinical measurement". Lancet 1 (8476): 307–10. doi:10.1016/S0140-6736(86)90837-8. PMID 2868172. 
  4. ^ R. J. Light, D. B. Pillemer (1984). Summing up: The Science of Reviewing Research. Cambridge, Massachusetts.: Harvard University Press. 
  5. ^ M. Egger, G. Davey Smith, M. Schneider & C. Minder (September 1997). "Bias in meta-analysis detected by a simple, graphical test". BMJ 315 (7109): 629–624. doi:10.1136/bmj.315.7109.629. PMC 2127453. PMID 9310563. 
  6. ^ Galbraith, Rex (1988). "Graphical display of estimates having differing standard errors". Technometrics (American Society for Quality) 30 (3): 271–281. doi:10.2307/1270081. JSTOR 1270081. 
  7. ^ Utts, Jessica M. Seeing Through Statistics 3rd Edition, Thomson Brooks/Cole, 2005, pp 166-167. ISBN 0-534-39402-7
  8. ^ Theodore T. Allen (2010). Introduction to Engineering Statistics and Lean Sigma: Statistical Quality Control and Design of Experiments and Systems. Springer. p. 128. ISBN 978-1-84882-999-2. Retrieved 2011-02-17. 
  9. ^ Hintze Jerry L., Nelson Ray D. (1998). "Violin Plots: A Box Plot-Density Trace Synergism". The American Statistician 52 (2): 181–84. doi:10.1080/00031305.1998.10480559. 

External links[edit]