Primer of Biostatistics, Seventh Edition PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Primer of Biostatistics, Seventh Edition PDF full book. Access full book title Primer of Biostatistics, Seventh Edition by Stanton Glantz. Download full books in PDF and EPUB format.
Author: Stanton Glantz
Publisher: McGraw Hill Professional
ISBN: 0071794409
Category : Medical
Languages : en
Pages : 327
Get Book Here
Book Description
A concise, engagingly written introduction to understanding statistics as they apply to medicine and the life sciences CD-ROM performs 30 statistical tests Don't be afraid of biostatistics anymore! Primer of Biostatistics,7th Edition demystifies this challenging topic in an interesting and enjoyable manner that assumes no prior knowledge of the subject. Faster than you thought possible, you'll understand test selection and be able to evaluate biomedical statistics critically, knowledgeably, and confidently. With Primer of Biostatistics, you’ll start with the basics, including analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems, culled from the recent biomedical literature, highlight the discussions throughout and help to foster a more intuitive approach to biostatistics. The companion CD-ROM contains everything you need to run thirty statistical tests of your own data. Review questions and summaries in each chapter facilitate the learning process and help you gauge your comprehension. By combining whimsical studies of Martians and other planetary residents with actual papers from the biomedical literature, the author makes the subject fun and engaging. Coverage includes: How to summarize data How to test for differences between groups The t test How to analyze rates and proportions What does “not significant” really mean? Confidence intervals How to test for trends Experiments when each subject receives more than one treatment Alternatives to analysis of variance and the t test based on ranks How to analyze survival data
Author: Stanton Glantz
Publisher: McGraw Hill Professional
ISBN: 0071794409
Category : Medical
Languages : en
Pages : 327
Get Book Here
Book Description
A concise, engagingly written introduction to understanding statistics as they apply to medicine and the life sciences CD-ROM performs 30 statistical tests Don't be afraid of biostatistics anymore! Primer of Biostatistics,7th Edition demystifies this challenging topic in an interesting and enjoyable manner that assumes no prior knowledge of the subject. Faster than you thought possible, you'll understand test selection and be able to evaluate biomedical statistics critically, knowledgeably, and confidently. With Primer of Biostatistics, you’ll start with the basics, including analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems, culled from the recent biomedical literature, highlight the discussions throughout and help to foster a more intuitive approach to biostatistics. The companion CD-ROM contains everything you need to run thirty statistical tests of your own data. Review questions and summaries in each chapter facilitate the learning process and help you gauge your comprehension. By combining whimsical studies of Martians and other planetary residents with actual papers from the biomedical literature, the author makes the subject fun and engaging. Coverage includes: How to summarize data How to test for differences between groups The t test How to analyze rates and proportions What does “not significant” really mean? Confidence intervals How to test for trends Experiments when each subject receives more than one treatment Alternatives to analysis of variance and the t test based on ranks How to analyze survival data
Author: Stanton Glantz
Publisher: McGraw-Hill Medical
ISBN: 9780071435093
Category : Medical
Languages : en
Pages : 550
Get Book Here
Book Description
Extremely popular, this student-friendly text presents the practical areas of statistics in terms of their relevance to medicine and the life sciences. Includes many illustrative examples and challenging problems that reinforce the author’s unique and intuitive approach to the subject. The new edition features a new two-color design, examples taken from current biomedical literature, and review questions within each chapter.
Author: Sylvia Wassertheil-Smoller
Publisher: Springer Science & Business Media
ISBN: 1475738870
Category : Science
Languages : en
Pages : 132
Get Book Here
Book Description
Biostatistics and Epidemiology/A Primer for Health Professionals offers practical guidelines and gives a concise framework for research and interpretation in the field. In addition to major sections covering statistics and epidemiology, the book includes a comprehensive exploration of scientific methodology, probability, and the clinical trial. The principles and methods described in this book are basic and apply to all medical subspecialties, psychology and education. The primer will be especially useful to public health officials and students looking for an understandable treatment of the subject.
Author: Michael S. Kramer
Publisher: Springer Science & Business Media
ISBN: 3642613721
Category : Science
Languages : en
Pages : 309
Get Book Here
Book Description
Here is a book for clinicians, clinical investigators, trainees, and graduates who wish to develop their proficiency in the planning, execution, and interpretation of clinical and epidemiological research. Emphasis is placed on the design and analysis of research studies involving human subjects where the primary interest concerns principles of analytic (cause-and- effect) inference. The topic is presented from the standpoint of the clinician and assumes no previous knowledge of epidemiology, research design or statistics. Extensive use is made of illustrative examples from a variety of clinical specialties and subspecialties. The book is divided into three parts. Part I deals with epidemiological research design and analytic inference, including such issues as measurement, rates, analytic bias, and the main forms of observational and experimental epidemiological studies. Part II presents the principles and applications of biostatistics, with emphasis on statistical inference. Part III comprises four chapters covering such topics as diagnostic tests, decision analysis, survival (life-table) analysis, and causality.
Author: Stanton A. Glantz
Publisher: McGraw Hill Professional
ISBN: 0071811834
Category : Medical
Languages : en
Pages : 980
Get Book Here
Book Description
Applicable for all statistics courses or practical use, teaches how to understand more advanced multivariate statistical methods, as well as how to use available software packages to get correct results. Study problems and examples culled from biomedical research illustrate key points. New to this edition: broadened coverage of ANOVA (traditional analysis of variance), the addition of ANCOVA (analysis of Co-Variance); updated treatment of available statistics software; 2 new chapters (Analysis of Variance Extensions and Mixing Regression and ANOVA: ANCOVA).
Author: Gregg Hartvigsen
Publisher: Columbia University Press
ISBN: 0231537042
Category : Education
Languages : en
Pages : 245
Get Book Here
Book Description
R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.
Author: Wayne W. Daniel
Publisher: Wiley
ISBN: 1119282373
Category : Medical
Languages : en
Pages : 720
Get Book Here
Book Description
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: Lisa M. Sullivan
Publisher: Jones & Bartlett Learning
ISBN: 1284194264
Category : Medical
Languages : en
Pages : 184
Get Book Here
Book Description
Written for undergraduate and graduate students with little or no mathematical background, Biostatistics for Population Health: A Primer offers current and future health professionals a clear, and accessible approach to learning the basic tools and techniques necessary to conduct biostatistical analyses and the professional confidence to critically evaluate and interpret biostatistical findings. Each unit begins with a contemporary population health issue (e.g., the opioid crisis, physical inactivity among children, diabetes) and raises questions that require the use of techniques discussed in that unit. Each technique, in turn, is illustrated with realistic, contemporary examples (e.g. vaping) to pique student interest. By the end of the unit, students are encouraged to apply the techniques to address the questions that were raised.
Author: Marcello Pagano
Publisher: CRC Press
ISBN: 0429952465
Category : Mathematics
Languages : en
Pages : 585
Get Book Here
Book Description
This edition is a reprint of the second edition published in 2000 by Brooks/Cole and then Cengage Learning. Principles of Biostatistics is aimed at students in the biological and health sciences who wish to learn modern research methods. It is based on a required course offered at the Harvard School of Public Health. In addition to these graduate students, many health professionals from the Harvard medical area attend as well. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them. All supplements, including a manual for students with solutions for odd-numbered exercises, a manual for instructors with solutions to all exercises, and selected data sets, are available at http://www.crcpress.com/9781138593145.
Author: Emmanuel Lesaffre
Publisher: John Wiley & Sons
ISBN: 0470018232
Category : Medical
Languages : en
Pages : 544
Get Book Here
Book Description
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics illustrated via a diverse range of applications taken from epidemiology, exploratory clinical studies, health promotion studies, image analysis and clinical trials. Key Features: Provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques. Contains introductory explanations of Bayesian principles common to all areas of application. Presents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics. Illustrated throughout with examples using software including WinBUGS, OpenBUGS, SAS and various dedicated R programs. Highlights the differences between the Bayesian and classical approaches. Supported by an accompanying website hosting free software and case study guides. Bayesian Biostatistics introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity. Master students in biostatistics, applied statisticians and all researchers with a good background in classical statistics who have interest in Bayesian methods will find this book useful.
