10.22376/ijpbs.2019.10.1.p1-12 Volume 6 Issue 3 2015 (July - September) In this paper, we have used the mathematical analysis to make a best linear model of the receptors of the survival proteins i.e. Epidermal growth factor (EGF) and Insulin using ten concentrations combinations. The model was made using different types of regression analysis in which regression coefficient ( lessThan i greaterThan r lessThan /i greaterThan lessThan sup greaterThan 2 lessThan /sup greaterThan ), adjusted regression coefficient ( lessThan i greaterThan r lessThan /i greaterThan lessThan sup greaterThan 2 lessThan /sup greaterThan lessThan sub greaterThan adj lessThan /sub greaterThan ),PRESS, regression coefficient, cross validation ( lessThan i greaterThan q lessThan /i greaterThan lessThan sup greaterThan 2 lessThan /sup greaterThan lessThan sub greaterThan cv lessThan /sub greaterThan ), Durban Watson statistics and other parameters was analyzed. We have plotted the probability density function (pdf) for normal distribution functions for the receptors i.e. lessThan i greaterThan epidermal growth factor receptor (EGFR) and insulin receptor (IRS) lessThan /i greaterThan which is coming OK. We have also plotted the survival function and hazard function for normal distribution function using different methods(kalpan meier and herd johnson) for maximum likelihood and least square methods. Non parametric functions were also plotted. SHRUTI JAIN AND DURG SINGH CHAUHAN EGF, Insulin, Receptors, Regression Analysis, probability distribution function, Anderson darling adjustment values. 164-176