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Possible Answers:
BLUE.
Last seen on: Daily Boston Globe Crossword Tuesday, 13 June 2023
Random information on the term “Cool color?”:
Chromostereopsis is a visual illusion whereby the impression of depth is conveyed in two-dimensional color images, usually of red–blue or red–green colors, but can also be perceived with red–grey or blue–grey images. Such illusions have been reported for over a century and have generally been attributed to some form of chromatic aberration.
Chromatic aberration results from the differential refraction of light depending on its wavelength, causing some light rays to converge before others in the eye (longitudinal chromatic aberration or LCA) and/or to be located on non-corresponding locations of the two eyes during binocular viewing (transverse chromatic aberration or TCA).
Chromostereopsis is usually observed using a target with red and blue bars and an achromatic background. Positive chromostereopsis is exhibited when the red bars are perceived in front of the blue and negative chromostereopsis is exhibited when the red bars are perceived behind the blue. Several models have been proposed to explain this effect which is often attributed to longitudinal and/or transverse chromatic aberrations. However, some work attributes most of the stereoptic effect to transverse chromatic aberrations in combination with cortical factors.
Random information on the term “BLUE”:
In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of the response given the values of the predictors, rather than on the joint probability distribution of all of these variables, which is the domain of multivariate analysis.