Thin plate and spherical splines are nonparametric methods suitable for spatial data analysis. Thin plate splines acquire efficient practical and high precision solutions in spatial interpolations. Two components in the model fitting is considered: spatial deviations of data and the model roughness. On the other hand, in parametric regression, the relationship between explanatory and response variables is considered as a functions based on minimizing sum of squares deviations criterion. In the current study, precision of the nonparametric methods that is thin plate spline and spherical spline is numerically compared with parametric multiple regression based on residual standard errors criterion by applying R software. Besides, precision of the fitted models is assessed for different sample sizes. Furthermore, the effect of different correlation coefficients is investigated by comparing precision of the fitted models for the three considered methods