Validation of n-variable Linear Regression Model


  • Anjay Kumar Mishra Madan Bhandari Memorial Academy
  • Krishna Kumar Chaudhary


Application, estimation, matrix, n variable, validation


Purpose: The researcher generalizes regression of three variables to n-variable by induction method
with the help of cofactor of a matrix so that it assist to the predictor and estimator to estimate and
predict dependent variable with the help of independent variables as applied in the relationship
between dependent variable GDP and independent variables agriculture, industry, and service sector
by using the n-variable regression model at initial condition. This seems a highly applied tool. So, its
verification for validity is most and it is attemped here. Design/methodology/approach: To verify the
n-variable linear model, both the methods are applied for the same data and estimated the best fit of
the line and checked after applying the correlation coefficient matrix method and multiple regression
equation using deviations from mean, zero order correlation coefficients, and standard deviation, do
the fluctuation existed in the line or not, is estimated. Findings/result: The estimation of dependent
variable with the help of independents variables can be estimated through the regression model found
to be valid. Originality/value: It is pure research and a useful tool for estimation for multiple
variables has been developed and validated.



How to Cite

Mishra, A. K., & Krishna Kumar Chaudhary. (2022). Validation of n-variable Linear Regression Model . NOLEGEIN-Journal of Operations Research &Amp; Management, 4(2), 26–29. Retrieved from