Statistical Tools In Human Biology Proceedings Of The 17th Course Of The International School Of Mathematics G Stampacchia
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Statistical Tools In Human Biology - Proceedings Of The 17th Course Of The International School Of Mathematics “G Stampacchia” by M Di Bacco,S Borgognini Tarli,E Pacciani Pdf
Advanced techniques of statistical inference are proposed for applications in human biology research. Major subjects concern classification and diagnosis, with special regard to the Bayesian approach. The effectiveness of such tools is tested by examples drawn from the concrete research work in the biological field. Great emphasis is placed on the use of expert systems.
Methods and Applications of Statistics in the Life and Health Sciences by Narayanaswamy Balakrishnan Pdf
Inspired by the Encyclopedia of Statistical Sciences, Second Edition, this volume outlines the statistical tools for successfully working with modern life and health sciences research Data collection holds an essential part in dictating the future of health sciences and public health, as the compilation of statistics allows researchers and medical practitioners to monitor trends in health status, identify health problems, and evaluate the impact of health policies and programs. Methods and Applications of Statistics in the Life and Health Sciences serves as a single, one-of-a-kind resource on the wide range of statistical methods, techniques, and applications that are applied in modern life and health sciences in research. Specially designed to present encyclopedic content in an accessible and self-contained format, this book outlines thorough coverage of the underlying theory and standard applications to research in related disciplines such as biology, epidemiology, clinical trials, and public health. Uniquely combining established literature with cutting-edge research, this book contains classical works and more than twenty-five new articles and completely revised contributions from the acclaimed Encyclopedia of Statistical Sciences, Second Edition. The result is a compilation of more than eighty articles that explores classic methodology and new topics, including: Sequential methods in biomedical research Statistical measures of human quality of life Change-point methods in genetics Sample size determination for clinical trials Mixed-effects regression models for predicting pre-clinical disease Probabilistic and statistical models for conception Statistical methods are explored and applied to population growth, disease detection and treatment, genetic and genomic research, drug development, clinical trials, screening and prevention, and the assessment of rehabilitation, recovery, and quality of life. These topics are explored in contributions written by more than 100 leading academics, researchers, and practitioners who utilize various statistical practices, such as election bias, survival analysis, missing data techniques, and cluster analysis for handling the wide array of modern issues in the life and health sciences. With its combination of traditional methodology and newly developed research, Methods and Applications of Statistics in the Life and Health Sciences has everything students, academics, and researchers in the life and health sciences need to build and apply their knowledge of statistical methods and applications.
Statistical Methods in Bioinformatics by Warren J. Ewens,Gregory R. Grant Pdf
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
Statistical Methods in Biology by Norman T. J. Bailey Pdf
Generations of biologists have relied on this useful book, which presents the basic concepts of statistics lucidly and convincingly. It recognizes that students must be aware of when to use standard techniques and how to apply the results they obtain. Because many biologists do not have a strong mathematical background, the arguments are gauged in terms that can be easily understood by those with only an elementary knowledge of algebra. Mathematical derivations are avoided and formulae are only used as a convenient shorthand. Although the subject is presented with great simplicity, the coverage is wide and will satisfy the needs of those working in many disciplines. New material for this third edition includes consideration of pocket electronic calculators and a special chapter devoted to a discussion of problems associated with numerical calculation, electronic calculators, and computers.
Biostatistics by Ronald N. Forthofer,Eun Sul Lee Pdf
The Biostatistics course is often found in the schools of public Health, medical schools, and, occasionally, in statistics and biology departments. The population of students in these courses is a diverse one, with varying preparedness. The book assumes the reader has at least two years of high school algebra, but no previous exposure to statistics is required. Written for individuals who might be fearful of mathematics, this book minimizes the technical difficulties and emphasizes the importance of statistics in scientific investigation. An understanding of underlying design and analysis is stressed. The limitations of the research, design and analytical techniques are discussed, allowing the reader to accurately interpret results. Real data, both processed and raw, are used extensively in examples and exercises. Statistical computing packages - MINITAB, SAS and Stata - are integrated. The use of the computer and software allows a sharper focus on the concepts, letting the computer do the necessary number-crunching. * Emphasizes underlying statistical concepts more than competing texts * Focuses on experimental design and analysis, at an elementary level * Includes an introduction to linear correlation and regression * Statistics are central: probability is downplayed * Presents life tables and survival analysis * Appendix with solutions to many exercises * Special instructor's manual with solution to all exercises
Statistical Methods in the Biological and Health Sciences by Janet Susan Milton,Janice O. Tsokos Pdf
Milton's Statistical Methods in the Biological and Health Sciences offers comprehensive coverage for the applied statistics course for health and bio-related majors. This course focuses primarily on developing basic statistical techniques and relevant applications within a framework that addresses the needs of these specific audiences.
Mathematical and Statistical Methods for Genetic Analysis by Kenneth Lange Pdf
Written to equip students in the mathematical siences to understand and model the epidemiological and experimental data encountered in genetics research. This second edition expands the original edition by over 100 pages and includes new material. Sprinkled throughout the chapters are many new problems.
Introduction to Nonparametric Statistics for the Biological Sciences Using R by Thomas W. MacFarland,Jan M. Yates Pdf
This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.
Applied Statistics for Network Biology by Matthias Dehmer,Frank Emmert-Streib,Armin Graber,Armindo Salvador Pdf
The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.
Statistical Models and Methods for Biomedical and Technical Systems by Filia Vonta,M.S. Nikulin,Nikolaos Limnios,Catherine Huber-Carol Pdf
This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics. The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.
Author : Robert C. Elston,Jaya M. Satagopan,Shuying Sun Publisher : Humana Press Page : 564 pages File Size : 54,5 Mb Release : 2016-08-23 Category : Science ISBN : 149395895X
Statistical Human Genetics by Robert C. Elston,Jaya M. Satagopan,Shuying Sun Pdf
Recent advances in genetics over the last quarter of a century, especially in molecular techniques, have dramatically reduced the cost of determining genetic markers and hence opened up a field of research that is increasingly helping to detect, prevent and/or cure many diseases that afflict humans. In Statistical Human Genetics: Methods and Protocols expert researchers in the field describe statistical methods and computer programs in the detail necessary to make them more easily accessible to the beginner analyzing data. Written in the highly successful Methods in Molecular BiologyTM series format, with examples of running the programs and interpreting the program outputs, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results from human genetic data collected in the laboratory. Thorough and as much as possible intuitive, Statistical Human Genetics: Methods and Protocols aids scientists in understanding the computer programs and analytical procedures they need to use.
