error of variance
61Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… …
62Statistical hypothesis testing — This article is about frequentist hypothesis testing which is taught in introductory statistics. For Bayesian hypothesis testing, see Bayesian inference. A statistical hypothesis test is a method of making decisions using data, whether from a… …
63Degrees of freedom (statistics) — In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary.[1] Estimates of statistical parameters can be based upon different amounts of information or data. The number… …
64Errors and residuals in statistics — For other senses of the word residual , see Residual. In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of the deviation of a sample from its theoretical value . The error of a… …
65Propagation of uncertainty — In statistics, propagation of uncertainty (or propagation of error) is the effect of variables uncertainties (or errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have… …
66Lack-of-fit sum of squares — In statistics, a sum of squares due to lack of fit, or more tersely a lack of fit sum of squares, is one of the components of a partition of the sum of squares in an analysis of variance, used in the numerator in an F test of the null hypothesis… …
67Factor analysis — is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved, uncorrelated variables called factors. In other words, it is possible, for example, that variations in …
68Orthogonality principle — In statistics and signal processing, the orthogonality principle is a necessary and sufficient condition for the optimality of a Bayesian estimator. Loosely stated, the orthogonality principle says that the error vector of the optimal estimator… …
69Control chart — One of the Seven Basic Tools of Quality First described by Walter A. Shewhart …
70Nonlinear regression — See Michaelis Menten kinetics for details In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or… …
