Cost Estimation Process for Construction Residential Projects by Using Multifactor Linear Regression Technique

Cost estimation in early stage plays an important role in the achievement of any construction project. Cost estimating is an assessment of the expected cost of any construction project. The accuracy of such estimate has a serious effect on the expected profit of the construction contractor. Hence, a certain contingency percentage should be added to the base estimate to improve the level of confidence. The process of cost estimating is materially affected by many factors. This paper aims to built a mathematical model for predicting the cost estimation for the residential construction projects. Multifactor linear regression technique is developed and used for predication of the cost of residential projects in Iraq. Ten effectiveness factors are used for cost estimation forecasting by (MLR) model, they include, experience of estimator, market status economic instability, accuracy of bidding documents, site condition and total area of residential building, the height of residential building, project location, type of residential building, estimating method. It was found that Multifactor linear regression has the flexibility to foretell the cost with a excellent degree of accuracy 91.76 %, mean absolute percentage error 8.240 % and coefficient of correlation (R) was 95.74 %.