A construction estimate is derived by determining all the materials, labor, equipment, etc. needed to complete a project and matching those quantities with the cost of each, adding all the costs together, plus a percentage for profit and overhead for the company. An estimate is usually submitted as a bid to do the work, but could be much more informal for a small job such as an addition of a house or a small garage. As with most things, the more detailed the estimator is in his work, the more accurate an estimate will be.
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A construction consulting would be used to determine scopes of work and repair estimates, to assist with dispute resolution, and to help with management of construction services.
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Advantages: The estimates of the unknown parameters obtained from linear least squares regression are the optimal. Estimates from a broad class of possible parameter estimates under the usual assumptions are used for process modeling. It uses data very efficiently. Good results can be obtained with relatively small data sets. The theory associated with linear regression is well-understood and allows for construction of different types of easily-interpretable statistical intervals for predictions, calibrations, and optimizations. Disadvantages: Outputs of regression can lie outside of the range [0,1]. It has limitations in the shapes that linear models can assume over long ranges The extrapolation properties will be possibly poor It is very sensitive to outliers It often gives optimal estimates of the unknown parameters.
geometric construction