Road construction analysis using regression technique

Estimating cost in construction is important to the city's design and planning management hence, estimate must not be overpriced which may cause corruption or underpricing that leads unreliable low-quality road projects. The total estimated only valid same year it was proposed because of inflation rate costs change. researchers applied Multiple Linear Regression technique predicting for analysis. model evaluated by means R-squared determine variables if they are correlated overfitting. calculated equals 0.696598 with predictor (x1 & x2) Roadbed width Net length predictors (Xi) explain 69.7% variance Y. higher result, better fit model. It also shows X1 X2 significant variables. coefficient multiple correlation (R) 0.834624 there a very strong between predicted data observed whereas dependent variable (y) Estimated cost. CCS CONCEPTS: • Construction Estimation Engineering