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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.
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.
Box plot Correlogram Histogram Line chart Scatterplot Violin plot; ADaMSoft: Yes Yes Yes Yes Yes Yes Alteryx: Yes Yes Yes Yes Yes Analyse-it: Yes Yes Yes Yes Yes Yes BMDP: Yes Yes ELKI: No No No Yes Yes Yes Epi Info: Yes No No Yes Yes Yes EViews: Yes Yes Yes Yes Yes Yes GAUSS: Yes Yes Yes Yes Yes GenStat: Yes Yes Yes Yes Yes Yes GraphPad Prism ...
The box plot above, using the CLD methodology, is now far more informative. The cities are sorted in descending order from left to right. The color density is tiered with the cities having higher rainfall being colored with more dense or opaque tones; meanwhile, the cities with lower rainfall have less dense or more transparent tones.
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."
Since the data ordering in the contour boxplot is from the center outwards, the 50% central region is defined by the band delimited by the 50% of deepest, or the most central observations. The border of the 50% central region is defined as the envelope representing the box in a classical boxplot.
MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities.
Another method of grouping the data is to use some qualitative characteristics instead of numerical intervals. For example, suppose in the above example, there are three types of students: 1) Below normal, if the response time is 5 to 14 seconds, 2) normal if it is between 15 and 24 seconds, and 3) above normal if it is 25 seconds or more, then the grouped data looks like: