Multivariate Data Analysis for Root Cause Analyses and Time-of-Flight Secondary Ion Mass Spectrometry
Autor Danica Heller-Krippendorfen Limba Engleză Paperback – 15 noi 2019
Danica Heller-Krippendorf develops concepts and approaches optimizing the applicability of MVA on data sets from an industrial context. They enable more time-efficient MVA of the respective ToF‑SIMS data. Priority is given to two main aspects by the author: First, the focus is on strategies for a more time-efficient collection of the input data. This includes the optimal selection of the number of replicate measurements, the selection of input data and guidelines for the selection appropriate data preprocessing methods. Second, strategies for more efficient analysis of MVA results are presented.
About the Author:Danica Heller-Krippendorf did her research and dissertation at the University of Siegen, Germany, in collaboration with a German analytical service company. Now she is engineer in analytics at a DAX company.Preț: 479.60 lei
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Specificații
ISBN-13: 9783658285012
ISBN-10: 365828501X
Pagini: 195
Ilustrații: XIX, 195 p. 66 illus., 6 illus. in color.
Dimensiuni: 148 x 210 mm
Greutate: 0.26 kg
Ediția:1st ed. 2019
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Locul publicării:Wiesbaden, Germany
ISBN-10: 365828501X
Pagini: 195
Ilustrații: XIX, 195 p. 66 illus., 6 illus. in color.
Dimensiuni: 148 x 210 mm
Greutate: 0.26 kg
Ediția:1st ed. 2019
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Locul publicării:Wiesbaden, Germany
Cuprins
Advantages of Correlation Loadings for MVA of ToF-SIMS Spectra.- Required Number of Replicate Measurements in an Industrial Context.- Selection of Suitable Data Pre-processing in Root Cause Analysis Including the Selection of an Efficient Peak List, Scaling, Normalization and Centering.- New Presentation of PCA Results in Order to Simplify Data Analysis.
Notă biografică
Danica Heller-Krippendorf did her research and dissertation at the University of Siegen, Germany, in collaboration with a German analytical service company. Now she is engineer in analytics at a DAX company.
Textul de pe ultima copertă
Danica Heller-Krippendorf develops concepts and approaches optimizing the applicability of MVA on data sets from an industrial context. They enable more time-efficient MVA of the respective ToF SIMS data. Priority is given to two main aspects by the author: First, the focus is on strategies for a more time-efficient collection of the input data. This includes the optimal selection of the number of replicate measurements, the selection of input data and guidelines for the selection appropriate data preprocessing methods. Second, strategies for more efficient analysis of MVA results are presented.
Contents
- Advantages of Correlation Loadings for MVA of ToF-SIMS Spectra
- Required Number of Replicate Measurements in an Industrial Context
- Selection of Suitable Data Pre-processing in Root Cause Analysis Including the Selection of an Efficient Peak List, Scaling, Normalization and Centering
- New Presentation of PCA Results in Order to Simplify Data Analysis
Target Groups
- Scientists and students in the field of surface analysis, data evaluation, ToF-SIMS and methods of multivariate data analysis
- Practitioners, especially in industry, in the field of surface and error analysis
About the Author
Danica Heller-Krippendorf did her research and dissertation at the University of Siegen, Germany, in collaboration with a German analytical service company. Now she is engineer in analytics at a DAX company.
Caracteristici
Strategies to more efficiency in To. F-SIMS data analysis