linear regression, rectilinear regression(noun)
the relation between variables when the regression equation is linear: e.g., y = ax + b
In statistics, linear regression is an approach to modeling the relationship between a scalar dependent variable y and one or more explanatory variables denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, it is called multiple linear regression. In linear regression, data are modeled using linear predictor functions, and unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, linear regression refers to a model in which the conditional mean of y given the value of X is an affine function of X. Less commonly, linear regression could refer to a model in which the median, or some other quantile of the conditional distribution of y given X is expressed as a linear function of X. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of y given X, rather than on the joint probability distribution of y and X, which is the domain of multivariate analysis.
The numerical value of linear regression in Chaldean Numerology is: 8
The numerical value of linear regression in Pythagorean Numerology is: 8
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"linear regression." Definitions.net. STANDS4 LLC, 2017. Web. 11 Dec. 2017. <http://www.definitions.net/definition/linear regression>.