@article{Mishra_Krishna Kumar Chaudhary_2022, title={Validation of n-variable Linear Regression Model }, volume={4}, url={https://mbajournals.in/index.php/JoORM/article/view/840}, abstractNote={<p>Purpose: The researcher generalizes regression of three variables to n-variable by induction method <br>with the help of cofactor of a matrix so that it assist to the predictor and estimator to estimate and <br>predict dependent variable with the help of independent variables as applied in the relationship <br>between dependent variable GDP and independent variables agriculture, industry, and service sector <br>by using the n-variable regression model at initial condition. This seems a highly applied tool. So, its <br>verification for validity is most and it is attemped here. Design/methodology/approach: To verify the <br>n-variable linear model, both the methods are applied for the same data and estimated the best fit of <br>the line and checked after applying the correlation coefficient matrix method and multiple regression <br>equation using deviations from mean, zero order correlation coefficients, and standard deviation, do <br>the fluctuation existed in the line or not, is estimated. Findings/result: The estimation of dependent <br>variable with the help of independents variables can be estimated through the regression model found <br>to be valid. Originality/value: It is pure research and a useful tool for estimation for multiple <br>variables has been developed and validated.</p>}, number={2}, journal={NOLEGEIN-Journal of Operations Research & Management}, author={Mishra, Anjay Kumar and Krishna Kumar Chaudhary}, year={2022}, month={Jan.}, pages={26–29} }