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Author : Mr. Y. I. Shah Dr. A. R. Paradkar,Mr. M. G. Dhayagude
Publisher : Pragati Books Pvt. Ltd.
Page : 296 pages
File Size : 54,9 Mb
Release : 2008-09-07
Category : Electronic
ISBN : 8185790337
Author : Babak Shahbaba
Publisher : Springer Science & Business Media
Page : 355 pages
File Size : 54,6 Mb
Release : 2011-12-15
Category : Medical
ISBN : 9781461413028
Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation. The book explains basic statistical concepts with a simple yet rigorous language. The development of ideas is in the context of real applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of this book is an introduction to Bayesian analysis. This author discusses basic statistical analysis through a series of biological examples using R and R-Commander as computational tools. The book is ideal for instructors of basic statistics for biologists and other health scientists. The step-by-step application of statistical methods discussed in this book allows readers, who are interested in statistics and its application in biology, to use the book as a self-learning text.
Author : Stewart Anderson
Publisher : CRC Press
Page : 328 pages
File Size : 43,5 Mb
Release : 2011-12-20
Category : Mathematics
ISBN : 9781584888345
The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25 years, broadening the landscape of available tools in statistical investigations of complex data. Biostatistics: A Computing Approach focuses on visualization and computational approaches associated with both modern and classical techniques. Furthermore, it promotes computing as a tool for performing both analyses and simulations that can facilitate such understanding. As a practical matter, programs in R and SAS are presented throughout the text. In addition to these programs, appendices describing the basic use of SAS and R are provided. Teaching by example, this book emphasizes the importance of simulation and numerical exploration in a modern-day statistical investigation. A few statistical methods that can be implemented with simple calculations are also worked into the text to build insight about how the methods really work. Suitable for students who have an interest in the application of statistical methods but do not necessarily intend to become statisticians, this book has been developed from Introduction to Biostatistics II, which the author taught for more than a decade at the University of Pittsburgh.
Author : Michael R. Chernick,Robert H. Friis
Publisher : John Wiley & Sons
Page : 426 pages
File Size : 42,9 Mb
Release : 2003-06-24
Category : Mathematics
ISBN : 9780471458654
"Introductory Biostatistics for the Health Sciences" ist eine fundierte Einführung in die Biostatistik und ihre Anwendungsgebiete. Der Band richtet sich vorwiegend an Mediziner und Statistiker. Theorie und Praxis stehen im ausgewogenen Verhältnis, d.h. praktische Anwendungen werden, wo nötig, durch den theoretischen Hintergrund ergänzt. Der Schwerpunkt liegt eindeutig auf der praktischen Anwendung. Der Band geht auch auf jüngste Fortschritte bei der Bootstrap-, Outlier- und Meta-Analyse ein, Themen, die in der Regel in Konkurrenzwerken, nicht behandelt werden. Mit einer Fülle von Übungsaufgaben. Auch Statistiksoftware wird ausführlich besprochen.
Author : Ronald N. Forthofer,Eun Sul Lee
Publisher : Elsevier
Page : 586 pages
File Size : 52,9 Mb
Release : 2014-05-19
Category : Mathematics
ISBN : 9781483296746
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. Introduction to Biostatistics 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
Author : Chap T. Le,Lynn E. Eberly
Publisher : John Wiley & Sons
Page : 626 pages
File Size : 50,7 Mb
Release : 2016-05-02
Category : Medical
ISBN : 9780470905401
Maintaining the same accessible and hands-on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real-world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields. Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials. This extensive update of Introductory Biostatistics, Second Edition includes: • A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs • A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes • R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software • Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts • Notes on Computations sections to provide further guidance on the use of software • A related website that hosts the large data sets presented throughout the book Introductory Biostatistics, Second Edition is an excellent textbook for upper-undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.
Author : N Gurumani
Publisher : MJP Publisher
Page : 250 pages
File Size : 40,8 Mb
Release : 101-01-17
Category : Science
ISBN : 9788180942563
Anthology containing: Introduction Population and Sample variables Collection of data classification and tabulation of data DIAGRAMS AND GRAPHS Frequency Distribution Descriptive Statistics scriv Measures of Central Tendency Averages Measures of Dispersion Skewness and Kurtosis Inferential statistics Probability Theoretical Probability Distributions Chi-Square Test Binomial Distribution Poisson Distribution Normal Distribution Inference About Population Sampling Methods Hypothesis Testing Student’s t-Test Analysis of Variance Correlation Regression Demography Computer Applications in Biology Number Systems Computer Codes Organisation of a Computer Computer Program Language Computer Memory and Storage Devices Operating System and Application Programs MS Excel—Statistical Functions Appendix References
Author : Steve Figard
Publisher : SAS Institute
Page : 229 pages
File Size : 51,7 Mb
Release : 2019-10-04
Category : Computers
ISBN : 9781635267181
Explore biostatistics using JMP® in this refreshing introduction Presented in an easy-to-understand way, Introduction to Biostatistics with JMP® introduces undergraduate students in the biological sciences to the most commonly used (and misused) statistical methods that they will need to analyze their experimental data using JMP. It covers many of the basic topics in statistics using biological examples for exercises so that the student biologists can see the relevance to future work in the problems addressed. The book starts by teaching students how to become confident in executing the right analysis by thinking like a statistician then moves into the application of specific tests. Using the powerful capabilities of JMP, the book addresses problems requiring analysis by chi-square tests, t tests, ANOVA analysis, various regression models, DOE, and survival analysis. Topics of particular interest to the biological or health science field include odds ratios, relative risk, and survival analysis. The author uses an engaging, conversational tone to explain concepts and keep readers interested in learning more. The book aims to create bioscientists who can competently incorporate statistics into their investigative toolkits to solve biological research questions as they arise.
Author : Thomas W. MacFarland
Publisher : Springer Science & Business Media
Page : 172 pages
File Size : 40,8 Mb
Release : 2013-11-19
Category : Medical
ISBN : 9783319025322
Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a basic understanding of R. Topics include: an introduction to Biostatistics and R, data exploration, descriptive statistics and measures of central tendency, t-Test for independent samples, t-Test for matched pairs, ANOVA, correlation and linear regression, and advice for future work.
Author : Thomas Glover,Kevin Mitchell
Publisher : Waveland Press
Page : 553 pages
File Size : 55,8 Mb
Release : 2015-06-29
Category : Mathematics
ISBN : 9781478631118
For over a decade, Glover and Mitchell have provided life-sciences students with an accessible, complete introduction to the use of statistics in their disciplines. The authors emphasize the relationships between probability, probability distributions, and hypothesis testing using both parametric and nonparametric analyses. Copious examples throughout the text apply concepts and theories to real questions faced by researchers in biology, environmental science, biochemistry, and health sciences. Dozens of examples and problems are new to the Third Edition, as are “Concept Checks”—short questions that allow readers to immediately gauge their mastery of the topics presented. Regardless of mathematical background, all readers will appreciate the value of statistics as a fundamental quantitative skill for the life sciences.
Author : Warren J. Ewens,Gregory R. Grant
Publisher : Springer Science & Business Media
Page : 616 pages
File Size : 48,8 Mb
Release : 2005-09-30
Category : Science
ISBN : 9780387400822
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)
Author : Ralph B. D'Agostino,Lisa Marie Sullivan,Alexa S. Beiser
Publisher : Brooks/Cole Publishing Company
Page : 652 pages
File Size : 45,8 Mb
Release : 2006
Category : Mathematics
ISBN : 053442399X
INTRODUCTORY APPLIED BIOSTATISTICS (WITH CD-ROM) explores statistical applications in the medical and public health fields. Examples drawn directly from the authors' clinical experiences with applied biostatistics make this text both practical and applicable. You'll master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results. This book is a must-have for every student preparing for a statistical career in a healthcare field!
Author : David Forsyth
Publisher : Springer
Page : 367 pages
File Size : 43,8 Mb
Release : 2017-12-13
Category : Computers
ISBN : 9783319644103
This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science features: • A treatment of random variables and expectations dealing primarily with the discrete case. • A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains. • A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing. • A chapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors. • A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems. • A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. • A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals. Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know. Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.
Author : Wayne W. Daniel,Chad L. Cross
Publisher : Wiley
Page : 720 pages
File Size : 45,8 Mb
Release : 2018-11-13
Category : Medical
ISBN : 9781119282372
The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.
Author : Christophe Lalanne,Mounir Mesbah
Publisher : Elsevier
Page : 174 pages
File Size : 51,8 Mb
Release : 2017-06-22
Category : Computers
ISBN : 9780081011713
This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands. Presents the use of SAS software in the statistical approach for the management of data modeling Includes elements of the language and descriptive statistics Supplies measures of association, comparison of means, and proportions for two or more samples Explores linear and logistic regression Provides survival data analysis