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Figure 2. Box-plot with whiskers from minimum to maximum Figure 3. Same box-plot with whiskers drawn within the 1.5 IQR value. A boxplot is a standardized way of displaying the dataset based on the five-number summary: the minimum, the maximum, the sample median, and the first and third quartiles.
A boxplot may also indicate which observations, if any, might be considered outliers. Carpet plot : A two-dimensional plot that illustrates the interaction between two and three independent variables and one to three dependent variables. Comet plot : A two- or three-dimensional animated plot in which the data points are traced on the screen.
It is possible to quickly compare several sets of observations by comparing their five-number summaries, which can be represented graphically using a boxplot. In addition to the points themselves, many L-estimators can be computed from the five-number summary, including interquartile range, midhinge, range, mid-range, and trimean.
The normal distribution is NOT assumed nor required in the calculation of control limits. Thus making the IndX/mR chart a very robust tool. This is demonstrated by Wheeler using real-world data [4], [5] and for a number of highly non-normal probability distributions.
MagicPlot is a technical plotting, curve fitting and data analysis application. It provides a wide usage of the graphical user interface for data exploration as well as various statistical analysis tools, peak fitting options, raster or vector formats of publishable plots.
To construct a contour boxplot, data ordering is the first step. In functional data analysis, each observation is a real function, therefore data ordering is different from the classical boxplot where scalar data are simply ordered from the smallest sample value to the largest. More generally, data depth, gives a center-outward ordering of data ...
In statistical graphics, the functional boxplot is an informative exploratory tool that has been proposed for visualizing functional data. [ 1 ] [ 2 ] Analogous to the classical boxplot , the descriptive statistics of a functional boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope.
The first scatterplot is formed from the points (d 1 α u 1i, d 2 α u 2i), for i = 1,...,n. The second plot is formed from the points (d 1 1−α v 1j, d 2 1−α v 2j), for j = 1,...,p. This is the biplot formed by the dominant two terms of the SVD, which can then be represented in a two-dimensional display.