plot, sometimes to a more general class of plots, and sometimes to the less commonly used P–P plot. The probability plot correlation coefficient plot...

The probability plot correlation coefficient (PPCC) plot is a graphical technique for identifying the shape parameter for a distributional family that...

error Probability of precipitation Probability plot Probability plot correlation coefficient – redirects to Q–Q plot Probability plot correlation coefficient...

plot, "quantile–quantile" plot Normal probability plot, a Q–Q plot against the standard normal distribution Probability plot correlation coefficient Probability...

In statistics, the Pearson correlation coefficient (PCC) is a correlation coefficient that measures linear correlation between two sets of data. It is...

A correlation coefficient is a numerical measure of some type of linear correlation, meaning a statistical relationship between two variables. The variables...

In statistics, Spearman's rank correlation coefficient or Spearman's ρ is a number ranging from -1 to 1 that indicates how strongly two sets of ranks...

distribution is more common than looking at a box plot, it can be useful to compare the box plot against the probability density function (theoretical histogram)...

In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's τ coefficient (after the Greek letter τ, tau), is a statistic...

product-moment correlation coefficient (PPMCC), or "Pearson's correlation coefficient", commonly called simply "the correlation coefficient". It is obtained...

from the real class) and their geometric mean is the Matthews correlation coefficient.[citation needed] Whereas ROC AUC varies between 0 and 1 — with...

np-chart p-chart Pie chart Probability plot Normal probability plot Poincaré plot Probability plot correlation coefficient plot Q–Q plot Rankit Run chart Seasonal...

A violin plot is a statistical graphic for comparing probability distributions. It is similar to a box plot, with the addition of a rotated kernel density...

scatter plot and many other statistical tools to pursue a scientific basis for eugenics. When, in 1886, Galton published a scatter plot and correlation ellipse...

binary variables. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class)...

A ridgeline plot (also known as a joyplot) is a series of line plots that are combined by vertical stacking to allow the easy visualization of changes...

to the kernel density. Sina plots are similar to violin plots, but while violin plots depict kernel density, sina plots depict the points themselves...

correlated in the population). An example is the Pearson product-moment correlation coefficient, which is found by dividing the covariance of the two variables...

In probability theory and statistics, the coefficient of variation (CV), also known as normalized root-mean-square deviation (NRMSD), percent RMS, and...

normalize the autocovariance function to get a time-dependent Pearson correlation coefficient. However, in other disciplines (e.g. engineering) the normalization...

tetrachoric correlation coefficient but it is only applicable to 2 × 2 tables. Polychoric correlation is an extension of the tetrachoric correlation to tables...

a volcano plot is a type of scatter-plot that is used to quickly identify changes in large data sets composed of replicate data. It plots significance...

recall), or the Matthews correlation coefficient, which is a geometric mean of the chance-corrected variants: the regression coefficients Informedness (DeltaP')...

In probability theory and statistics, partial correlation measures the degree of association between two random variables, with the effect of a set of...

joint-probability of agreement, such as Cohen's kappa, Scott's pi and Fleiss' kappa; or inter-rater correlation, concordance correlation coefficient, intra-class...

that plot data as the maximal total area, can be applied to sort the variables (axes) into relative positions that reveal distinct correlations, trade-offs...

contrast, the marginal effect of xj on y can be assessed using a correlation coefficient or simple linear regression model relating only xj to y; this effect...

A funnel plot is a graph designed to check for the existence of publication bias; funnel plots are commonly used in systematic reviews and meta-analyses...

size will be the signal energy. In probability and statistics, the term cross-correlations refers to the correlations between the entries of two random...

In probability theory, the tail dependence of a pair of random variables is a measure of their comovements in the tails of the distributions. The concept...