Multivariate linear regression is about fitting the observed data to some multidimensional surface - a formula is postulated which purportedly defines how an explanatory variable is related to a response variable. The response variable being the 'observed result/response' that the scientist hopes to model with the formula and the set of explanatory variables being the variables, which in conjunction with the formula, can be used to 'explain' the result.
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