Comparison of the accuracy of experimental data approximation using the least relative squares method with the least squares method

The results of comparing the accuracy of approximation of experimental or tabular data obtained using the standard method of least squares (LSM) and the proposed method of least relative squares (LRSM), for example, a given table dependence of the viscosity of a water-glycerine solution on the mass concentration of glycerol. The advantage of the latter is shown as the sum and average values of the local relative deviation of calculated data of viscosity of the desired solution obtained by LRSM, with similar data obtained by standard LSM and maximum values of these relative deviations. So, calculated using LSM average relative deviations of theoretical viscosity of an aqueous solution of glycerin from the specified table, in absolute value equal to 12.9%; LRSM of 5.8%, i.e., below 2 times. Accordingly the largest relative deviations in the LSM are 17.9%, and LRSM – 10.6 %, that is, reduced by 68%. It is proposed to determine the conditional values of parallel experiments based on the experimental data of the main experiment. To do this, the calculation of conditional numerical values of the i-th parallel experience is determined by the method of piecewise linear approximation of i-1 and i+1 numerical values of the main experience or table data. A correlation analysis is performed to determine the correlation coefficients, reproducibility, adequacy, and significance of the coefficients of the resulting regression equation.

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