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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.
Bar chart 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 ...
The normal deviate mapping (or normal quantile function, or inverse normal cumulative distribution) is given by the probit function, so that the horizontal axis is x = probit(P fa) and the vertical is y = probit(P fr), where P fa and P fr are the false-accept and false-reject rates.
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.
For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.
Mosaic plot showing cross-sectional distribution through time of different musical themes in the Guardian's list of "1000 songs to hear before you die". A mosaic plot , Marimekko chart , Mekko chart , or sometimes percent stacked bar plot , is a graphical visualization of data from two or more qualitative variables. [ 1 ]
A non-exhaustive list of software implementations of Empirical Distribution function includes: In R software, we compute an empirical cumulative distribution function, with several methods for plotting, printing and computing with such an “ecdf” object. In MATLAB we can use Empirical cumulative distribution function (cdf) plot