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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.
Quartile. In statistics, quartiles are a type of quantiles which divide the number of data points into four parts, or quarters, of more-or-less equal size. The data must be ordered from smallest to largest to compute quartiles; as such, quartiles are a form of order statistic. The three quartiles, resulting in four data divisions, are as follows:
Boxplot (with an interquartile range) and a probability density function (pdf) of a Normal N (0,σ2) Population. In descriptive statistics, the interquartile range (IQR) is a measure of statistical dispersion, which is the spread of the data. [ 1 ] The IQR may also be called the midspread, middle 50%, fourth spread, or H‑spread.
Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.
Functional boxplot. 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 ...
Medcouple. A histogram of 5000 random values sampled from a skew gamma distribution above, and the corresponding histogram of the medcouple kernel values below. The actual medcouple is the median of the bottom distribution, marked at 0.188994 with a yellow line. In statistics, the medcouple is a robust statistic that measures the skewness of a ...
The border of the 50% central region is defined as the envelope representing the box in a classical boxplot. Thus, this 50% central region is the analog to the interquartile range (IQR) and gives a useful indication of the spread of the central 50% of the curves. This is a robust range for interpretation because the 50% central region is not ...
Q–Q plot for first opening/final closing dates of Washington State Route 20, versus a normal distribution. [5] Outliers are visible in the upper right corner. A Q–Q plot is a plot of the quantiles of two distributions against each other, or a plot based on estimates of the quantiles. The pattern of points in the plot is used to compare the ...