Buch, Englisch, Band 34, 528 Seiten, Format (B × H): 173 mm x 247 mm, Gewicht: 1005 g
Buch, Englisch, Band 34, 528 Seiten, Format (B × H): 173 mm x 247 mm, Gewicht: 1005 g
Reihe: Oxford Statistical Science Series
ISBN: 978-0-19-929659-0
Verlag: Oxford University Press
The second part presents a more detailed discussion of the general theory and of a wide variety of experiments. The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations. The mathematical theory of the designs is
developed in parallel with their construction in SAS, so providing motivation for the development of the subject. Many chapters cover self-contained topics drawn from science, engineering and pharmaceutical investigations, such as response surface designs, blocking of experiments, designs for mixture experiments and for nonlinear and generalized linear models. Understanding is aided by the provision of "SAS tasks" after most chapters as well as by more traditional exercises and a fully
supported website. The authors are leading experts in key fields and this book is ideal for statisticians and scientists in academia, research and the process and pharmaceutical industries.
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Prozedurale Programmierung
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Präventivmedizin, Gesundheitsförderung, Medizinisches Screening
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung