Basic Statistics for the Health Sciences

Basic Statistics for the Health Sciences PDF

Author: Jan W. Kuzma

Publisher: McGraw-Hill Europe

Published: 2005

Total Pages: 0

ISBN-13: 9780071112482

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This is the only introductory statistics text written specifically for health science students. Assuming no prerequisites other than high school algebra, the authors provide numerous examples from health settings, a wealth of helpful learning aids, as well as hundreds of exercises to help students succeed in the course.

Basic Statistics for the Health Sciences

Basic Statistics for the Health Sciences PDF

Author: Jan W. Kuzma

Publisher:

Published: 2001

Total Pages: 392

ISBN-13:

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An introductory statistics text written specifically for health science students. It assumes no prerequisites other than high school algebra, the authors provide numerous examples from health settings, a wealth of helpful learning aids, as well as hundreds of exercises to help students succeed in the course. Contents 1. Statistics and How They Are Used 2. Populations and Samples 3. Organizing and Displaying Data 4. Summarizing Data 5. Probability 6. The Normal Distribution 7. Sampling Distribution of Means 8. Sample Significance Testing, Point Estimates, and Confidence Intervals 9. Two Sample Significance Testing, Point Estimates, and Confidence Intervals 10. Analysis of Variance, ANOVA 11. Inferences Regarding Proportions 12. The Chi-Square Test 13. Correlation and Linear Regression 14. Nonparametric Methods 15. Vital Statistics and Demographic Methods 16. Life Tables 17. The Health Survey and the Research Report Appendix A: Binomial Probability Table Appendix B: P ...

Statistics for the Health Sciences

Statistics for the Health Sciences PDF

Author: Christine Dancey

Publisher: SAGE

Published: 2012-03-19

Total Pages: 588

ISBN-13: 1446291235

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Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae. The textbook takes students from the basics of research design, hypothesis testing and descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter. The strengths and weaknesses of different techniques are critically appraised throughout, and the authors emphasise how they may be used both in research and to inform best practice care in health settings. Exercises and tips throughout the book allow students to practice using SPSS. The companion website provides further practical experience of conducting statistical analyses. Features include: • multiple choice questions for both student and lecturer use • full Powerpoint slides for lecturers • practical exercises using SPSS • additional practical exercises using SAS and R This is an essential textbook for students studying beginner and intermediate level statistics across the health sciences.

Introductory Statistics for the Health Sciences

Introductory Statistics for the Health Sciences PDF

Author: Lise DeShea

Publisher: CRC Press

Published: 2015-03-25

Total Pages: 578

ISBN-13: 1466565349

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Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets from published research. Examples come from many area

Statistics in the Health Sciences

Statistics in the Health Sciences PDF

Author: Albert Vexler

Publisher: CRC Press

Published: 2018-01-19

Total Pages: 416

ISBN-13: 1315293765

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"This very informative book introduces classical and novel statistical methods that can be used by theoretical and applied biostatisticians to develop efficient solutions for real-world problems encountered in clinical trials and epidemiological studies. The authors provide a detailed discussion of methodological and applied issues in parametric, semi-parametric and nonparametric approaches, including computationally extensive data-driven techniques, such as empirical likelihood, sequential procedures, and bootstrap methods. Many of these techniques are implemented using popular software such as R and SAS."— Vlad Dragalin, Professor, Johnson and Johnson, Spring House, PA "It is always a pleasure to come across a new book that covers nearly all facets of a branch of science one thought was so broad, so diverse, and so dynamic that no single book could possibly hope to capture all of the fundamentals as well as directions of the field. The topics within the book’s purview—fundamentals of measure-theoretic probability; parametric and non-parametric statistical inference; central limit theorems; basics of martingale theory; Monte Carlo methods; sequential analysis; sequential change-point detection—are all covered with inspiring clarity and precision. The authors are also very thorough and avail themselves of the most recent scholarship. They provide a detailed account of the state of the art, and bring together results that were previously scattered across disparate disciplines. This makes the book more than just a textbook: it is a panoramic companion to the field of Biostatistics. The book is self-contained, and the concise but careful exposition of material makes it accessible to a wide audience. This is appealing to graduate students interested in getting into the field, and also to professors looking to design a course on the subject." — Aleksey S. Polunchenko, Department of Mathematical Sciences, State University of New York at Binghamton This book should be appropriate for use both as a text and as a reference. This book delivers a "ready-to-go" well-structured product to be employed in developing advanced courses. In this book the readers can find classical and new theoretical methods, open problems and new procedures. The book presents biostatistical results that are novel to the current set of books on the market and results that are even new with respect to the modern scientific literature. Several of these results can be found only in this book.

Applied Statistics for the Social and Health Sciences

Applied Statistics for the Social and Health Sciences PDF

Author: Rachel A. Gordon

Publisher: Taylor & Francis

Published: 2023-11-15

Total Pages: 800

ISBN-13: 1000894738

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For graduate students in the social and health sciences, featuring essential concepts and equations most often needed in scholarly publications. Uses excerpts from the scholarly literature in these fields to introduce new concepts. Uses publicly-available data that are regularly used in social and health science publications to introduce Stata code and illustrate concepts and interpretation. Thoroughly integrates the teaching of statistical theory with teaching data processing and analysis. Offers guidance about planning projects and organizing code for reproducibility Shows how to recognize critiques of the constructions, terminology, and interpretations of statistics. New edition focuses on Stata, with code integrated into the chapters (rather than appendices, as in the first edition) includes Stata’s factor variables and margins commands and Long and Freese’s (2014) spost13 commands, to simplify programming and facilitate interpretation.

Basic Statistics for Social Research

Basic Statistics for Social Research PDF

Author: Robert A. Hanneman

Publisher: John Wiley & Sons

Published: 2012-12-04

Total Pages: 560

ISBN-13: 0470587989

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A core statistics text that emphasizes logical inquiry, not math Basic Statistics for Social Research teaches core general statistical concepts and methods that all social science majors must master to understand (and do) social research. Its use of mathematics and theory are deliberately limited, as the authors focus on the use of concepts and tools of statistics in the analysis of social science data, rather than on the mathematical and computational aspects. Research questions and applications are taken from a wide variety of subfields in sociology, and each chapter is organized around one or more general ideas that are explained at its beginning and then applied in increasing detail in the body of the text. Each chapter contains instructive features to aid students in understanding and mastering the various statistical approaches presented in the book, including: Learning objectives Check quizzes after many sections and an answer key at the end of the chapter Summary Key terms End-of-chapter exercises SPSS exercises (in select chapters) Ancillary materials for both the student and the instructor are available and include a test bank for instructors and downloadable video tutorials for students.

Using Basic Statistics in the Behavioral and Social Sciences

Using Basic Statistics in the Behavioral and Social Sciences PDF

Author: Annabel Ness Evans

Publisher: SAGE Publications

Published: 2013-06-06

Total Pages: 605

ISBN-13: 1483323617

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In this fully updated edition of Using Basic Statistics in the Behavioral and Social Sciences, Annabel Ness Evans presents introductory statistics in a practical, conceptual, and humorous way, reducing the anxiety that many students experience in introductory courses. Avoiding complex notation and derivations, the book focuses on helping readers develop an understanding of the underlying logic of statistics, rather than rote memorization. Focus on Research boxes engage students with realistic applications of statistics, and end-of-chapter exercises ensure student comprehension. This exciting new edition includes a greater number of realistic and engaging global examples within the social and behavioral sciences, making it ideal for use within many departments or in interdisciplinary settings.

Statistics for Health Data Science

Statistics for Health Data Science PDF

Author: Ruth Etzioni

Publisher: Springer Nature

Published: 2021-01-04

Total Pages: 238

ISBN-13: 3030598896

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Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students’ anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/