Linear Model Analysis of Observational Data in the Sense of Least –Squares Criterion

J.A. Basabrain^1,

¹Department of Statistics College of Science for Girls, King Abdulaziz University, Jeddah, Saudi Arabia

Cite this paper:
J.A. Basabrain. Linear Model Analysis of Observational Data in the Sense of Least –Squares Criterion. American Journal of Mathematical Analysis. 2015; 3(2):47-53. doi: 10.12691/ajma-3-2-5

Abstract

The present paper is devoted for the following goals: To develop an algorithm for model analysis of observational data in the sense of the least –squares criterion with full error analysis.. By this algorithm one computes, all the solutions with their variances, the variance of the fit, the average square distance between the least square solution and the exact solution, and graphical representation between the row and the fitted data. Mathematica module of the algorithm was established, through five points, its purpose –input - output –needed procedures and the list of the module. By this paper we have been tried to produce an error controlled algorithm of the least squares method for observational data.

Keywords:
statistical data analysis -least squares method mathematica simulations

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References:

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