Regression Analysis

adjusted analysis of variance application appropriate approximate assumed b₁ calculated Chapter column combined comparison concurrence considered constant correction correlation corresponding covariance curve degrees of freedom density departure dependent derived determined deviation direct discriminant function discussed distribution effect elements equal error estimate example experiment experimental fact factor fiducial limits fitted formulas function given gives groups Hence hypothesis included independent variables interest inverse matrix known linear matrix maximum mean square measured method multiple regression null observed origin over-all parameters polynomial possible practical present problem range ratio reduced regression coefficients regression equation regression lines regression sum relationship residual residual sum restriction sample shown shows significance significance tests simple specimens squares and products standard error Statistics strength sum of squares Table taken temperature treatment usually values variation weight x₁ zero ΣΣ