Title
Modern Statistics for Modern Biology,Used
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If you are a biologist and want to get the best out of the powerful methods of modern computational statistics, this is your book. You can visualize and analyze your own data, apply unsupervised and supervised learning, integrate datasets, apply hypothesis testing, and make publicationquality figures using the power of R/Bioconductor and ggplot2. This book will teach you 'cooking from scratch', from raw data to beautiful illuminating output, as you learn to write your own scripts in the R language and to use advanced statistics packages from CRAN and Bioconductor. It covers a broad range of basic and advanced topics important in the analysis of highthroughput biological data, including principal component analysis and multidimensional scaling, clustering, multiple testing, unsupervised and supervised learning, resampling, the pitfalls of experimental design, and power simulations using Monte Carlo, and it even reaches networks, trees, spatial statistics, image data, and microbial ecology. Using a minimum of mathematical notation, it builds understanding from wellchosen examples, simulation, visualization, and above all handson interaction with data and code.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the size and binding of this book? A: The book measures eight and a half inches by ten and three-quarters inches and is available in paperback binding.
- Q: How many pages does this book have? A: This book contains four hundred two pages, providing extensive coverage of modern statistical methods.
- Q: Who is the author of this book? A: The author of this book is Susan Holmes, a recognized expert in computational statistics.
- Q: What statistical topics does this book cover? A: The book covers a wide range of topics, including principal component analysis, clustering, and hypothesis testing.
- Q: Is this book suitable for beginners in statistics? A: Yes, this book is suitable for beginners as it starts with basic concepts and progresses to advanced topics.
- Q: Do I need prior knowledge of R to understand this book? A: No, prior knowledge of R is not required, as the book teaches you how to use R from the ground up.
- Q: How can I apply the methods learned from this book? A: You can apply the methods by visualizing and analyzing your own biological data using R and Bioconductor.
- Q: Is this book suitable for someone outside the biology field? A: Yes, while it is tailored for biologists, the statistical methods can be beneficial to anyone interested in data analysis.
- Q: How should I store this book to keep it in good condition? A: Store this book in a cool, dry place, away from direct sunlight to prevent damage to the cover and pages.
- Q: Can I return the book if I am not satisfied? A: Yes, you can return the book within the specified return policy period if you are not satisfied with your purchase.
- Q: What if the book arrives damaged? A: If the book arrives damaged, contact customer service for a replacement or refund according to their policy.
- Q: Does this book include hands-on examples? A: Yes, the book includes hands-on examples and simulations to enhance understanding of statistical concepts.
- Q: Is there a focus on specific software in this book? A: Yes, the book focuses on using R, Bioconductor, and ggplot2 for statistical analysis and visualization.
- Q: What is the main goal of this book? A: The main goal of this book is to empower biologists to effectively use modern computational statistics in their research.
- Q: Will I learn about advanced statistical techniques? A: Yes, the book covers advanced techniques such as power simulations and spatial statistics.