# The binary correlation coefficient measures

Two binary variables are considered positively associated if most of the data falls along the diagonal cells. In contrast, two binary variables are considered negatively associated if most of the data falls off the diagonal.

The phi coefficient that describes the association of x and y is. The phi coefficient has a maximum value that is determined by the distribution of the two variables if one or both variables can take on more than two values.

See Davenport El-Sanhury [5] for a thorough discussion. From Wikipedia, the free encyclopedia. Mathematical Methods of Statistics. Princeton University Press, p. Equating r-based and d-based effect-size indices: Problems with a commonly recommended formula. Educational and Psychological Measurement, 51, — Mean arithmetic geometric harmonic Median Mode. Central limit theorem Moments Skewness Kurtosis L-moments. Grouped data Frequency distribution Contingency table. Pearson product-moment correlation Rank correlation Spearman's rho Kendall's tau Partial correlation Scatter plot.

Sampling stratified cluster Standard error Opinion poll Questionnaire. National Council on Measurement in Education. Retrieved April 17, A statistic used to show how the scores from one measure relate to scores on a second measure for the same group of individuals. A low negative value approaching Statistical methods in practice: Mean arithmetic geometric harmonic Median Mode. Central limit theorem Moments Skewness Kurtosis L-moments.

Grouped data Frequency distribution Contingency table. Pearson product-moment correlation Rank correlation Spearman's rho Kendall's tau Partial correlation Scatter plot. Sampling stratified cluster Standard error Opinion poll Questionnaire. Observational study Natural experiment Quasi-experiment. Z -test normal Student's t -test F -test. Bayesian probability prior posterior Credible interval Bayes factor Bayesian estimator Maximum posterior estimator.

Pearson product-moment Partial correlation Confounding variable Coefficient of determination. Simple linear regression Ordinary least squares General linear model Bayesian regression. Regression Manova Principal components Canonical correlation Discriminant analysis Cluster analysis Classification Structural equation model Factor analysis Multivariate distributions Elliptical distributions Normal.

Spectral density estimation Fourier analysis Wavelet Whittle likelihood.