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Basic & Clinical Biostatistics / Susan E. White
New York : McGraw-Hill, 2019
vii, 358 pages. : illustrations ; 25 cm.
Ký hiệu phân loại (DDC): 616
Basic & Clinical Biostatistics introduces the medical student, researcher, or practitioner to the study of statistics applied to medicine and other disciplines in the health field. The book covers the basics of biostatistics and quantitative methods in epidemiology and the clinical applications in evidence-based medicine and the decision-making methods. Particular emphasis is on study design and interpretation of results of research
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Biostatistics : a foundation for analysis in the health sciences / Wayne W. Daniel, Chad Lee Cross
NJ, Hoboken : Wiley, 2019
xix, 695 pages : illustrations ; 26 cm.
Ký hiệu phân loại (DDC): 610.727
The ability to analyze and interpret vast amounts of data has become a prerequisite for success in the healthcare and health sciences fields, Biostatistics: Analytical Foundations in the Health Sciences cont. continues to provide in-depth instruction in the concepts, techniques, and practical applications of biostatistics in the modern healthcare environment. Comprehensive in scope yet detailed in content, this text helps students understand - and appropriately use - probability distributions, sampling distributions, estimation, hypothesis testing, and analysis of variance. error, regression, correlation analysis, and other basic statistical tools for the science and practice of medicine.
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Biostatistics : a foundation for analysis in the health sciences / Wayne W. Daniel, Chad Lee Cross
Hoboken, NJ : Wiley, 2013
956 tr. : illustrations ; 24 cm
Ký hiệu phân loại (DDC): 610.727
This 10th edition of Biostatistics: A Foundation for Analysis in the Health Sciences was prepared with the objective of appealing to a wide audience. Previous editions of the book have been used by the authors and their colleagues in a variety of contexts. For under-graduates, this edition should provide an introduction to statistical concepts for students inthe biosciences, health sciences, and for mathematics majors desiring exposure to applied statistical concepts. Like its predecessors, this edition is designed to meet the needs ofbeginning graduate students in various fields such as nursing, applied sciences, and public health who are seeking a strong foundation in quantitative methods. For professionals already working in the health field, this edition can serve as a useful desk reference.
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Introductory biological statistics / John Edward Havel, Raymond E. Hampton, Scott J. Meiners
Long Grove, Illinois : Waveland Press, Inc., 2019
x, 252 pages. : illustrations ; 28 cm.
Ký hiệu phân loại (DDC): 570.1
A thorough understanding of biology, no matter which subfield, requires a thorough understanding of statistics. As in previous editions, Havel and Hampton (with new co-author Scott Meiners) ground students in all essential methods of descriptive and inferential statistics, using examples from different biological sciences. The authors have retained the readable, accessible writing style popular with both students and instructors. Pedagogical improvements new to this edition include concept checks in all chapters to assist students in active learning and code samples showing how to solve many of the book’s examples using R. Each chapter features numerous practice and homework exercises, with larger data sets available for download.
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Using R for biostatistics / Thomas W. MacFarland, Jan M. Yates
Cham, Switzerland : Springer, 2021
929 pages. : illustrations (some color) ; cm.
Ký hiệu phân loại (DDC): 570.15195
This book introduces the open source R software language that can be implemented in biostatistics for data organization, statistical analysis, and graphical presentation. In the years since the authors' 2014 work Introduction to Data Analysis and Graphical Presentation in Biostatistics with R, the R user community has grown exponentially and the R language has increased in maturity and functionality. This updated volume expands upon skill-sets useful for students and practitioners in the biological sciences by describing how to work with data in an efficient manner, how to engage in meaningful statistical analyses from multiple perspectives, and how to generate high-quality graphics for professional publication of their research. A common theme for research in the diverse biological sciences is that decision-making depends on the empirical use of data. Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent samples and matched pairs; oneway and twoway analyses of variance; and correlation and linear regression. The authors also demonstrate the importance of a nonparametric perspective for quality assurance through chapters on the Mann-Whitney U Test, Wilcoxon Matched-Pairs Signed-Ranks test, Kruskal-Wallis H-Test for Oneway Analysis of Variance, and the Friedman Twoway Analysis of Variance. To address the element of data presentation, the book also provides an extensive review of the many graphical functions available with R. There are now perhaps more than 15,000 external packages available to the R community. The authors place special emphasis on graphics using the lattice package and the ggplot2 package, as well as less common, but equally useful, figures such as bean plots, strip charts, and violin plots. A robust package of supplementary material, as well as an introduction of the development of both R and the discipline of biostatistics, makes this ideal for novice learners as well as more experienced practitioners
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