A plot is a graphical technique for presenting a data set drawn by hand or produced by a mechanical or electronic plotter. It is a graph depicting the relationship between two or more variables used, for instance, in visualising scientific data.

Overview

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: NIST/SEMATECH (2003). "The Role of Graphics". In: e-Handbook of Statistical Methods 6/01/2003 (Date created).

• hypothesis testing
• analysis of variance
• point estimates and confidence intervals
• least squares regression

These and similar techniques are all valuable and are mainstream in terms of classical analysis. On the other hand, there is a large collection of statistical tools that we generally refer to as graphical techniques. These include:

• scatter plots
• histograms
• probability plots
• residual plots
• box plots, and
• block plots

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. If one is not using statistical graphics, then one is forfeiting insight into one or more aspects of the underlying structure of the data.

Types of plots

• Arrhenius plot : This plot displays the logarithm of a rate ($\backslash ln(k)$, ordinate axis) plotted against inverse temperature ($1/T$, abscissa). Arrhenius plots are often used to analyze the effect of temperature on the rates of chemical reactions.

• Biplot : These are a type of graph used in statistics. A biplot allows information on both samples and variables of a data matrix to be displayed graphically. Samples are displayed as points while variables are displayed either as vectors, linear axes or nonlinear trajectories. In the case of categorical variables, category level points may be used to represent the levels of a categorical variable. A generalised biplot displays information on both continuous and categorical variables.

• Bland-Altman plot : In analytical chemistry and biostatistics this plot is a method of data plotting used in analysing the agreement between two different assays. It is identical to a Tukey mean-difference plot, which is what it is still known as in other fields, but was popularised in medical statistics by Bland and Altman.