linear relation
61Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …
62Effect size — In statistics, an effect size is a measure of the strength of the relationship between two variables in a statistical population, or a sample based estimate of that quantity. An effect size calculated from data is a descriptive statistic that… …
63Multivariate stable distribution — multivariate stable Probability density function Heatmap showing a Multivariate (bivariate) stable distribution with α = 1.1 parameters: exponent shift/location vector …
64Covariance — This article is about the measure of linear relation between random variables. For other uses, see Covariance (disambiguation). In probability theory and statistics, covariance is a measure of how much two variables change together. Variance is a …
65Wronskian — In mathematics, the Wronskian is a function named after the Polish mathematician Józef Hoene Wroński. It is especially important in the study of differential equations, where it can be used to determine whether a set of solutions is linearly… …
66Aeroacoustics — is a branch of acoustics that studies noise generation via either turbulent fluid motion or aerodynamic forces interacting with surfaces. Noise generation can also be associated with periodically varying flows. Although no complete scientific… …
67Refractive index — Refraction of light at the interface between two media. In optics the refractive index or index of refraction of a substance or medium is a measure of the speed of light in that medium. It is expressed as a ratio of the speed of light in vacuum… …
68Companding — Original signal After compressing, before expanding In …
69Bipolar junction transistor — BJT redirects here. For the Japanese language proficiency test, see Business Japanese Proficiency Test. PNP …
70Errors-in-variables models — In statistics and econometrics, errors in variables models or measurement errors models are regression models that account for measurement errors in the independent variables. In contrast, standard regression models assume that those regressors… …
