applied statistics for the social and health sciences

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Applied Statistics For The Social And Health Sciences

Author : Rachel A. Gordon
ISBN : 9780415875363
Genre : Mathematics
File Size : 80. 96 MB
Format : PDF
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Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them. This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature thorough integration of teaching statistical theory with teaching data processing and analysis teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set. This book is for a two-semester course. For a one-semester course, see http://www.routledge.com/9780415991544/

Using Statistics In The Social And Health Sciences With Spss And Excel

Author : Martin Lee Abbott
ISBN : 9781119121046
Genre : Social Science
File Size : 52. 72 MB
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Provides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS® and Excel® applications This book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field. The book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material. Using Statistics in the Social and Health Sciences with SPSS® and Excel® includes: Use of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings Inclusion of a data lab section in each chapter that provides relevant, clear examples Introduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs Emphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS® and Excel® for analyzing data.

Vital Statistics E Book

Author : Stephen McKenzie
ISBN : 9780729581493
Genre : Medical
File Size : 63. 48 MB
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Vital Statistics: an introduction to health science statistics e-book is a new Australian publication. This textbook draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student. It demonstrates how an understanding of statistics is useful in the real world, as well as in statistics exams. Vital Statistics: an introduction to health science statistics e-book is a relatively easy-to-read book that will painlessly introduce or re-introduce you to the statistical basics before guiding you through more demanding statistical challenges. Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics. It explores: How data relates to information, and how information relates to knowledge How to use statistics to distinguish information from disinformation The importance of probability, in statistics and in life That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be How to appropriately apply and interpret statistical measures of difference and association How qualitative and quantitative methods differ, and when it’s appropriate to use each The special statistical needs of the health sciences, and some especially health science relevant statistics The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses Real-life local examples of health statistics are presented, e.g. A study conducted at the Department of Obstetrics and Gynecology, University of Utah School of Medicine, explored whether there might be a systematic bias affecting the results of genetic specimen tests, which could affect their generalizability. Reader-friendly writing style t-tests/ ANOVA family of inferential statistics all use variants of the same basic formula Learning Objectives at the start of each chapter and Quick Reference Summaries at the end of each chapter provide the reader with a scope of the content within each chapter.

Fundamental Statistics For The Social Behavioral And Health Sciences

Author : Miguel A. Padilla
ISBN : 1516555279
Genre : Business & Economics
File Size : 70. 40 MB
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Fundamental Statistics for the Social, Behavioral, and Health Sciences presents instructional material in a clear, concise way and features exercises that get students thinking about how to use statistics in applied settings. The text opens with an introduction to descriptive statistics which covers frequency distribution, central tendency, and variability. The chapters that follow take students through an introductory journey into inferential statistics. While many standard texts in the discipline overload students with information, Fundamental Statistics for the Social, Behavioral, and Health Sciences strategically presents information that is enhanced with clear examples and graphs. Rather than relying on memorized examples, students learn to apply what they learn to a variety of situations. The book includes step-by-step instructions on using IBM's Statistical Package for Social Sciences, so there is no need to purchase a separate text to master it.

Handbook Of Mixed Membership Models And Their Applications

Author : Edoardo M. Airoldi
ISBN : 9781466504097
Genre : Computers
File Size : 50. 11 MB
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In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.

Applied Statistics From Bivariate Through Multivariate Techniques

Author : Rebecca M. Warner
ISBN : 9781412991346
Genre : Mathematics
File Size : 59. 15 MB
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Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.

Statistics For The Health Sciences

Author : Christine Dancey
ISBN : 9781446291238
Genre : Social Science
File Size : 75. 49 MB
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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.

Introduction To Research In The Health Sciences E Book

Author : Stephen Polgar
ISBN : 9780702050169
Genre : Medical
File Size : 75. 70 MB
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Like the previous versions, the fifth edition of An Introduction to Research in the Health Sciences has two overall aims. 1) To introduce the fundamental principles of research methodology and explain how these principles are applied for conducting research in the health sciences. 2) To demonstrate how evidence produced through research is applied to solving problems in everday health care. This book is written in an accessible style. It maintains the traditions of the previous editions, with examples, questions, feedback sections, and an extensive glossary. Uses simple language and demystifies the jargon Provides built-in feedback for readers to assess their own progress Gives examples relating directly to the health sciences Provides an extensive glossary for better understanding of the language of research Addresses qualitative as well as quantitative research issues Includes a chapter focussing on the use of qualitative methods in health research Includes a chapter for discussing systematic reviews and meta-analyses Contains more revision questions Increased emphasis throughout on evidence based concepts More and updated discussion of qualitative research methods New section on basic epidemiological concepts as a research approach More discussion of analysis and use of administrative and secondary data sets as research resources Complete rewrite of the chapter on causal research Stronger links between the sections on different stages of research

Introductory Biostatistics For The Health Sciences

Author : Michael R. Chernick
ISBN : 9780471458654
Genre : Mathematics
File Size : 48. 83 MB
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Accessible to medicine- and/or public policy-related audiences, aswell as most statisticians. Emphasis on outliers is discussed by way of detection andtreatment. Resampling statistics software is incorporated throughout. Motivating applications are presented in light of honesttheory. Plentiful exercises are sprinkled throughout.

Applied Multivariate Statistics For The Social Sciences Fifth Edition

Author : James P. Stevens
ISBN : 9781136910692
Genre : Education
File Size : 83. 51 MB
Format : PDF, Kindle
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This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.

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