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Statistical Methods in the Biological and Health Sciences

Statistical Methods in the Biological and Health Sciences
Author: Janet Susan Milton
Publisher: McGraw-Hill Companies
Total Pages: 520
Release: 1983
Genre: Mathematics
ISBN:

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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.


Statistics with Applications to the Biological and Health Sciences

Statistics with Applications to the Biological and Health Sciences
Author: M. Anthony Schork
Publisher:
Total Pages: 504
Release: 2000
Genre: Business & Economics
ISBN:

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THE definitive basic book on applied biostatistical methods. Particularly suited for readers with limited mathematical background, it makes biostatistics accessible by using thorough, intuitive explanations (often laced with humor and described with an appeal to common sense logical notions), and by focusing on selected statistical methods and procedures applicable to the biological, biomedical, and health sciences. It discusses the concepts of the method, the rationale of the method, when to use the method, and how to interpret the results. The computations (while included) are not the focus of the presentation. Several larger examples are used repeatedly (from chapter to chapter) to demonstrate how investigators develop and carry out a study by moving from problem statement, to data accrual, to computation of descriptive statistics, to estimation and hypothesis testing, including univariate, bivariate and finally multivariable procedures for both discrete and continuous variables. The book is not tied to any particular computer package (e.g., SAS, Systat, BMDP), however manyprototype computerized outputs of statistical analyses are illustrated and discussedin detail , with guidelines for reading and interpreting results. Descriptive Statistics. Probability. Populations, Samples, and Inference. Some Important Distributions. Estimation. Hypothesis Testing. Frequency Data. The Analysis of Variance. Simple Linear Regression and Correlation. Multiple Regression. Logistic Regression. Repeated Measures and Longitudinal Studies. Distribution-Free and Nonparametric Methods. Demography and Vital Statistics. For anyone involved in the biological, biomedical, or health sciences.


Advances in Statistical Methods for the Health Sciences

Advances in Statistical Methods for the Health Sciences
Author: Jean-Louis Auget
Publisher: Springer Science & Business Media
Total Pages: 540
Release: 2007-08-08
Genre: Mathematics
ISBN: 081764542X

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Statistical methods have become an increasingly important and integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained comprehensive volume covers a wide range of topics pertaining to new statistical methods in the health sciences, including epidemiology, pharmacovigilance, quality of life, survival analysis, and genomics. The book will serve the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics.


Modern Statistical Methods for Health Research

Modern Statistical Methods for Health Research
Author: Yichuan Zhao
Publisher: Springer Nature
Total Pages: 506
Release: 2021-10-14
Genre: Medical
ISBN: 3030724379

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This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.


Applied Statistical Methods in Agriculture, Health and Life Sciences

Applied Statistical Methods in Agriculture, Health and Life Sciences
Author: Bayo Lawal
Publisher: Springer
Total Pages: 816
Release: 2014-09-15
Genre: Medical
ISBN: 3319055550

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This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examples is approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter.


Biostatistics for the Biological and Health Sciences

Biostatistics for the Biological and Health Sciences
Author: Marc M. Triola
Publisher:
Total Pages: 699
Release: 2018
Genre: Biometry
ISBN: 9780134039015

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For courses in Introductory Statistics Real-world applications connect statistical concepts to everyday life. Biostatistics for the Biological and Health Sciences uses a variety of real-world applications to bring statistical theories and methods to life. Through these examples and a friendly writing style, the 2nd Edition ensures that you understand concepts and develop skills in critical thinking, technology, and communication. The result of collaboration between a biological sciences expert and the author of the #1 statistics book in the country, Biostatistics for the Biological and Health Sciences provides an excellent introduction to statistics for readers interested in the biological, life, medical, and health sciences. Also available with MyLab Statistics MyLab(tm) Statistics is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. Note: You are purchasing a standalone product; MyLab(tm) does not come packaged with this content. Students, if interested in purchasing this title with MyLab, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab, search for: 0134768345 / 9780134768342 Biostatistics for the Biological and Health Sciences Plus MyLab Statistics with Pearson eText -- Title-Specific Access Card Package, 2/e Package consists of: 0134039017 / 9780134039015 Biostatistics for the Biological and Health Sciences 0134748875 / 9780134748870 MyLab Statistics with Pearson eText -- Standalone Access Card -- for Biostatistics for the Biological and Health Sciences


An Introduction to Statistical Analysis in Research, Optimized Edition

An Introduction to Statistical Analysis in Research, Optimized Edition
Author: Kathleen F. Weaver
Publisher: John Wiley & Sons
Total Pages: 616
Release: 2017-08-10
Genre: Mathematics
ISBN: 1119301106

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Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous j


Methods and Applications of Statistics in the Life and Health Sciences

Methods and Applications of Statistics in the Life and Health Sciences
Author: Narayanaswamy Balakrishnan
Publisher: John Wiley & Sons
Total Pages: 1027
Release: 2009-12-02
Genre: Mathematics
ISBN: 0470405090

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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 Design and Analysis of Biological Experiments

Statistical Design and Analysis of Biological Experiments
Author: Hans-Michael Kaltenbach
Publisher: Springer Nature
Total Pages: 281
Release: 2021-04-15
Genre: Mathematics
ISBN: 3030696413

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This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.