Applied Statistics for the Social and Health Sciences

Author: Rachel A. Gordon
Publisher: Routledge
ISBN: 0415875366
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

Fundamental Statistics for the Social Behavioral and Health Sciences First Edition

Author: Miguel a. Padilla
Publisher: Cognella Academic Publishing
ISBN: 9781516518906
Format: PDF, ePub, Docs
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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. Miguel A. Padilla earned his Ph.D. in research and evaluation methodology at the University of Florida, Gainesville and completed a postdoctoral fellowship in biostatistics at the University of Alabama at Birmingham. Dr. Padilla is an associate professor of quantitative psychology and faculty member in the Department of Psychology and the Department of Mathematics and Statistics at Old Dominion University. He has presented his research at numerous professional conferences and publishes extensively in various journals with work appearing in Educational and Psychological Measurement, the Journal of Modern Applied Statistical Methods, Violence Against Women, and Psychology of Women Quarterly.

Vital statistics E Book

Author: Stephen McKenzie
Publisher: Elsevier Health Sciences
ISBN: 0729581497
Format: PDF, Docs
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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.

Statistics for the Health Sciences

Author: Christine Dancey
Publisher: SAGE
ISBN: 1446291235
Format: PDF, ePub, Mobi
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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.

Handbook of Mixed Membership Models and Their Applications

Author: Edoardo M. Airoldi
Publisher: CRC Press
ISBN: 1466504099
Format: PDF, ePub
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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
Publisher: SAGE
ISBN: 141299134X
Format: PDF
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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.

SPSS for the Health and Behavioural Sciences

Author: Peter James Allen
Publisher: Nelson Australia
ISBN: 9780170135399
Format: PDF, ePub
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"SPSS is a flexible and efficient set of data analytic tools used widely throughout the health, social and behavioural sciences. This book aims to introduce to its readers a range of commonly used statistical procedures that can be performed with SPSS, and are typically included in the curricula of undergraduate applied statistics and research methodology units throughout the health, social and behavioural sciences."--Provided by publisher.

Using Statistics in Social Research

Author: Scott M. Lynch
Publisher: Springer Science & Business Media
ISBN: 1461485738
Format: PDF, ePub, Mobi
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This book covers applied statistics for the social sciences with upper-level undergraduate students in mind. The chapters are based on lecture notes from an introductory statistics course the author has taught for a number of years. The book integrates statistics into the research process, with early chapters covering basic philosophical issues underpinning the process of scientific research. These include the concepts of deductive reasoning and the falsifiability of hypotheses, the development of a research question and hypotheses, and the process of data collection and measurement. Probability theory is then covered extensively with a focus on its role in laying the foundation for statistical reasoning and inference. After illustrating the Central Limit Theorem, later chapters address the key, basic statistical methods used in social science research, including various z and t tests and confidence intervals, nonparametric chi square tests, one-way analysis of variance, correlation, simple regression, and multiple regression, with a discussion of the key issues involved in thinking about causal processes. Concepts and topics are illustrated using both real and simulated data. The penultimate chapter presents rules and suggestions for the successful presentation of statistics in tabular and graphic formats, and the final chapter offers suggestions for subsequent reading and study.

Applied Bayesian Modelling

Author: Peter Congdon
Publisher: Wiley
ISBN: 9780471486954
Format: PDF, ePub, Mobi
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The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author’s best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS – a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example – explaining fully the choice of model for each particular problem. The book · Provides a broad and comprehensive account of applied Bayesian modelling. · Describes a variety of model assessment methods and the flexibility of Bayesian prior specifications. · Covers many application areas, including panel data models, structural equation and other multivariate structure models, spatial analysis, survival analysis and epidemiology. · Provides detailed worked examples in WINBUGS to illustrate the practical application of the techniques described. All WINBUGS programs are available from an ftp site. The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis.