Average Reviews:
(More customer reviews)David Siegmund is a famous probabilist who is both a great lecturer and writer. I personally audited his advanced probability course at Stanford. He coauthored a book on optimal stopping with Herb Robbins and has written other fine books on sequential analysis and repeated significance testing. In recent years he as well as Brad Efron and other Stanford and Berkeley statistics professors has studied the mathematics, probability theory and statistics associated with human genetics and microarray data. This book presents the theory and application of the appropriate probabilistic methods. Anyone with a serious interest in this topic should get the book.
The book assumes some knowledge of probability and statistics. So a novice in the field of statistics could have trouble with the text and require more development. Also for the statistician it may assume a little too much knowledge of genetics. But I think it is the perfect book for the intended audience and makes a great reference.
Another text that is rigorous in terms of statistics and assume less knowledge of statistics and genetics is "Analyzing Microarray Gene Expression Data" by G. J. McLachlan, k.-A. Do and C. Amboise. You will find that I have also reviewed that text on amazon.
Click Here to see more reviews about: The Statistics of Gene Mapping (Statistics for Biology and Health)
This book details the statistical concepts used in gene mapping, first in the experimental context of crosses of inbred lines and then in outbred populations, primarily humans. It presents elementary principles of probability and statistics, which are implemented by computational tools based on the R programming language to simulate genetic experiments and evaluate statistical analyses. Each chapter contains exercises, both theoretical and computational, some routine and others that are more challenging. The R programming language is developed in the text.
0 comments:
Post a Comment