Reinschmidt kenneth (24 Ergebnisse)

Hardbound. Zustand: Good. Reprint. ex library with markings; 55 pages.

Paperback. Zustand: Brand New. 66 pages. 11.00x8.30x0.20 inches. In Stock.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Kartoniert / Broschiert. Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New. pp. 379.

Zustand: New.

Zustand: New.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Gebunden. Zustand: New.

Zustand: New.

Zustand: New.

Hardcover. Zustand: Brand New. 379 pages. 9.50x6.25x1.00 inches. In Stock.

Hardcover. Zustand: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Zustand: Very Good. First Edition. VG: in very good condition without dust jackets. Covers rubbed and marked; bowing to boards. 240mm x 160mm (9" x 6"). [viii], x, 748pp; [viii], iv, 1195pp; [viii], iv, 1091pp; [viii], iv, 956pp; [ix], iv, 1148pp. B/w illustrations. Volumes C, Ia, Ib, II, & III. Heavy set - extra shipping needed for overseas. Illustrated hardback yellow cloth covers. …

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a step-by-step guidance on how to implement analytical methods in project risk management.The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes.The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts' judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory.The book is organized in three parts and fourteen chapters. In Part I theauthors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution. 396 pp. Englisch.…

Zustand: New. Print on Demand pp. 379.

Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a step-by-step guidance on how to implement analytical methods in project risk management.The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes.The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts' judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory.The book is organized in three parts and fourteen chapters. In Part I theauthors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution. 396 pp. Englisch.…

Zustand: New. PRINT ON DEMAND pp. 379.

Zustand: New. PRINT ON DEMAND.