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

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

values and the values expected under the model Multiple correlation Partial correlation Correlation coefficient: A statistic used to show how the scores...

In statistics, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman and often denoted by the Greek letter ρ {\displaystyle...

Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function...

In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although...

In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This...

that there are large partial correlations compared to the sum of correlations. In other words, there are widespread correlations which would be a large...

In time series analysis, the partial autocorrelation function (PACF) gives the partial correlation of a stationary time series with its own lagged values...

"remarkable" correlations of the correlation matrix, by a solid line (positive correlation) or dotted line (negative correlation). A strong correlation is not...

Frequency distribution Grouped data Dependence Partial correlation Pearson product-moment correlation Rank correlation Kendall's τ Spearman's ρ Scatter plot Graphics...

"probability plot correlation coefficient" (PPCC plot) is the correlation coefficient between the paired sample quantiles. The closer the correlation coefficient...

are correlations among the variables, then canonical-correlation analysis will find linear combinations of X and Y that have a maximum correlation with...

two 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)...

characteristics of the data (estimation), describing associations within the data (correlation), and modeling relationships within the data (for example, using regression...

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

In statistics, a rank correlation is any of several statistics that measure an ordinal association—the relationship between rankings of different ordinal...

of correlation matrices. In other words, partial correlation vines provide an algebraically independent parametrization of the set of correlation matrices...

value of kappa as the calculation given above. Bangdiwala's B Intraclass correlation Krippendorff's alpha Statistical classification Banerjee, M.; Capozzoli...

\\0&&&\sigma _{x_{n}}\end{bmatrix}}} So, using the idea of partial correlation, and partial variance, the inverse covariance matrix can be expressed analogously:...

over time. Iconography of correlations consists in replacing a correlation matrix by a diagram where the “remarkable” correlations are represented by a solid...

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

of the other variable (possibly the independent variable) (see also correlation and simple linear regression). Bivariate analysis can be contrasted with...

Frequency distribution Grouped data Dependence Partial correlation Pearson product-moment correlation Rank correlation Kendall's τ Spearman's ρ Scatter plot Graphics...

groups and two dependent variables, MANOVA's power is lowest when the correlation equals the ratio of the smaller to the larger standardized effect size...

argued that since the humanities affirm knowledge production as "situated, partial, and constitutive," using data may introduce assumptions that are counterproductive...

network activity, the analysis is based on partial correlations. In simple words, the partial (or residual) correlation is a measure of the effect (or contribution)...

its associated items are partialed out. Thereafter, the average squared off-diagonal correlation for the subsequent correlation matrix is then computed...

to use an all positive correlations (APC) arrangement of the strongly correlated variables under which pairwise correlations among these variables are...

measure of rank correlation known as the rank-biserial correlation. Edward Cureton introduced and named the measure. Like other correlational measures, the...