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Modern Statistics for Modern Biology
Taschenbuch von Susan Holmes (u. a.)
Sprache: Englisch

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Beschreibung
A far-reaching course in practical advanced statistics for biologists using R/Bioconductor, data exploration, and simulation.
A far-reaching course in practical advanced statistics for biologists using R/Bioconductor, data exploration, and simulation.
Über den Autor
Susan Holmes is Professor of Statistics at Stanford University, California. She specializes in exploring and visualizing multidomain biological data, using computational statistics to draw inferences in microbiology, immunology and cancer biology. She has published over 100 research papers, and has been a key developer of software for the multivariate analyses of complex heterogeneous data. She was the Breiman Lecturer at NIPS 2016, has been named a Fields Institute fellow, and is currently a fellow at the Center for the Advances Study of the Behavioral Sciences.
Inhaltsverzeichnis
Introduction; 1. Generative models for discrete data; 2. Statistical modeling; 3. High-quality graphics in R; 4. Mixture models; 5. Clustering; 6. Testing; 7. Multivariate analysis; 8. High-throughput count data; 9. Multivariate methods for heterogeneous data; 10. Networks and trees; 11. Image data; 12. Supervised learning; 13. Design of high-throughput experiments and their analyses; Statistical concordance; Bibliography; Index.
Details
Erscheinungsjahr: 2019
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 402
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781108705295
ISBN-10: 1108705294
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Holmes, Susan
Huber, Wolfgang
Hersteller: Cambridge University Press
Maße: 280 x 220 x 24 mm
Von/Mit: Susan Holmes (u. a.)
Erscheinungsdatum: 28.02.2019
Gewicht: 1,128 kg
preigu-id: 116039538
Über den Autor
Susan Holmes is Professor of Statistics at Stanford University, California. She specializes in exploring and visualizing multidomain biological data, using computational statistics to draw inferences in microbiology, immunology and cancer biology. She has published over 100 research papers, and has been a key developer of software for the multivariate analyses of complex heterogeneous data. She was the Breiman Lecturer at NIPS 2016, has been named a Fields Institute fellow, and is currently a fellow at the Center for the Advances Study of the Behavioral Sciences.
Inhaltsverzeichnis
Introduction; 1. Generative models for discrete data; 2. Statistical modeling; 3. High-quality graphics in R; 4. Mixture models; 5. Clustering; 6. Testing; 7. Multivariate analysis; 8. High-throughput count data; 9. Multivariate methods for heterogeneous data; 10. Networks and trees; 11. Image data; 12. Supervised learning; 13. Design of high-throughput experiments and their analyses; Statistical concordance; Bibliography; Index.
Details
Erscheinungsjahr: 2019
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 402
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781108705295
ISBN-10: 1108705294
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Holmes, Susan
Huber, Wolfgang
Hersteller: Cambridge University Press
Maße: 280 x 220 x 24 mm
Von/Mit: Susan Holmes (u. a.)
Erscheinungsdatum: 28.02.2019
Gewicht: 1,128 kg
preigu-id: 116039538
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