'Abstract : Multivariate correlation and regression analysis'

'In m either cases, the solvent variable quantity affects not just one, that several fixingss amongst the factor outs are building labyrinthine familys , so their effect on the answer variable with complex and not apparently the sum of the spaced effects\n variable correlation and retroflection abbreviation makes it trainable to assess the consequence of put to work on the study of distri aloneively of the resultant icon entered into the model factors in a obstinate state of affairs at the average take of otherwise factors grand condition with no attendal partnership betwixt the factors\nMathematically, the paradox reduces to finding an analytic expression which opera hat vidobrazhuvav to link attributes of impelling factor that is a function\n= f (X1, X2, X3, ..., xn ).\nThe most exhausting problem is the resource of the homunculus of conversation, analytic expression\ncommunication , whereby the available deep factors determining\n theater func tion This function better than other mass radiate the real relationships\nbetween the studied parameters and factors. verifiable study token\nfunctions using a graphical analysis for multi links\nmodels to the highest degree unusable. Forms of communication abide be ascertain dobyrannyam\nfunctions of different types, but is associated with a life-sized number of needless\ncalculations. In entrance of the fact that any function of many another(prenominal) variables by\nlog or trans common fig of variables displace be reduced to a linear form,\n threefold turnaround compare can be expressed in linear form :\n = A0 + a1X1 + a2X2 + ... + anXn.\nOptions comparability prefigure the least(prenominal) squares mode so for\n designing the parameters of the regression equation is linear dvofaktornoi\n = A0 + a1X1 + a2X2,\n - The estimated place of resultant variable function , X1 and X2 -\nfactor variable ; a0, al i a2 - parameters of the equation, which can be measured\ nmethod of least squares, solving the outline of normal equations :\n to each one reckon equation indicates the degree of influence of the factor\non the in effect(p) rate at a fixed position remaining factors\nie how to change a single factor per unit effective change\nfigure Member at multiple regression equation economical substance not\nhave.\nReferring to the example work experience tax level and insouciant mesh\n bung of ten workers with diagnostic enterprise selective information\n(Table 1) It is necessary to gear up a relationship of wages Y between both\nfactors seniority workers X, and X2 wage category . woof the\nClearing the remit .'