Modern Statistics for Modern Biology
-10%
portes grátis
Modern Statistics for Modern Biology
Huber, Wolfgang; Holmes, Susan (Stanford University, California)
Cambridge University Press
02/2019
402
Mole
Inglês
9781108705295
15 a 20 dias
Designed for a new generation of biologists, this textbook teaches modern computational statistics by using R/Bioconductor to analyze experimental data from high-throughput technologies. The presentation minimizes mathematical notation and emphasizes inductive understanding from well-chosen examples, hands-on simulation, and visualization.
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.
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Designed for a new generation of biologists, this textbook teaches modern computational statistics by using R/Bioconductor to analyze experimental data from high-throughput technologies. The presentation minimizes mathematical notation and emphasizes inductive understanding from well-chosen examples, hands-on simulation, and visualization.
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
