Modern Statistics for the Life Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Modern Statistics for the Life Sciences write by Alan Grafen. This book was released on 2002-03-21. Modern Statistics for the Life Sciences available in PDF, EPUB and Kindle. Model formulae represent a powerful methodology for describing, discussing, understanding, and performing that large part of statistical tests known as linear statistics. The book aims to put this methodology firmly within the grasp of undergraduates.
Modern Statistics for Modern Biology
Modern Statistics for Modern Biology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Modern Statistics for Modern Biology write by SUSAN. HUBER HOLMES (WOLFGANG.). This book was released on 2018. Modern Statistics for Modern Biology available in PDF, EPUB and Kindle.
The Practice of Statistics in the Life Sciences
The Practice of Statistics in the Life Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Practice of Statistics in the Life Sciences write by Brigitte Baldi. This book was released on 2013-12-15. The Practice of Statistics in the Life Sciences available in PDF, EPUB and Kindle. This remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore’s The Basic Practice of Statistics, PSLS mirrors that #1 bestseller’s signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.
Statistical Research Methods in the Life Sciences
Statistical Research Methods in the Life Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Research Methods in the Life Sciences write by Pejaver Vishwamber Rao. This book was released on 1998. Statistical Research Methods in the Life Sciences available in PDF, EPUB and Kindle. Appropriate for all courses in statistical methods for the agricultural, life, health, and environmental sciences, this book offers a practical and modern approach that minimizes computation and emphasizes conceptual understanding. Rao continually emphasizes issues and topics most relevant to modern day research in the life sciences. For example, point and interval estimation take priority over testing of statistical hypothesis and methods and guidelines for determination of sample size are indicated whenever possible. Statistical Research Methods in the Life Sciences also presents a self-contained and complete discussion of each experimental situation considered. In the two-sample setting, for example, in addition to presenting the procedures under the usual analysis of variance assumption, Rao also presents methods for checking the validity of the assumptions.
Statistics for High-Dimensional Data
Statistics for High-Dimensional Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistics for High-Dimensional Data write by Peter Bühlmann. This book was released on 2011-06-08. Statistics for High-Dimensional Data available in PDF, EPUB and Kindle. Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.
