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126E

Expert-verifiedFound in: Page 803

Book edition
13th

Author(s)
James T. McClave, P. George Benson, Terry Sincich

Pages
888 pages

ISBN
9780134506593

**Accuracy of software effort estimates. Refer to the Journal of Empirical Software Engineering (Vol. 9, 2004) study of the accuracy of new software effort estimates, Exercise 12.114 (p. 781). Recall that stepwise regression was used to develop a model for the relative error in estimating effort (y) as a function of company role of estimator (x _{1} = 1 if developer, 0 if project leader) and previous accuracy (x_{8} = 1 if more than 20% accurate, 0 if less than 20% accurate). The stepwise regression yielded the prediction equation $\hat{y}{=}{0}{.}{12}{-}{0}{.}{28}{{x}}_{{1}}{+}{0}{.}{27}{{x}}_{{8}}$**

The estimated sign for β for x_{1} is positive (the developer has a larger relative error of estimation than a project leader) but the prediction equation estimated using step-wise regression is negative sign of x_{1}. A possible reason for the same could be the existence of multicollinearity in the model.

The estimated sign for β for x_{1} is positive (the developer has a larger relative error of estimation than a project leader) but the prediction equation estimated using step-wise regression is negative sign of x_{1}. A possible reason for the same could be the existence of multicollinearity in the model.

Since there is high degree of correlation amongst relative error in estimating effort (y) and company role of estimator (x_{1}) the β estimates will not be true parameter indicators and will be biased.

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