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Statistics and Data Analysis for Nursing Research

Statistics and Data Analysis for Nursing Research Author Denise F. Polit
ISBN-10 0135085071
Release 2010
Pages 440
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The second edition of Statistics and Data Analysis for Nursing , uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. Special focus is given to quantitative methods. Other features include management of data, how to "clean" data, and how to work around missing data. New to this edition are updated research examples utilizinging examples from an international mix of studies published by nurse researchers in 2006-2009.



Statistics and Data Analysis for Nursing Research

Statistics and Data Analysis for Nursing Research Author Denise Polit
ISBN-10 1256509396
Release 2010
Pages
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Statistics and Data Analysis for Nursing Research has been writing in one form or another for most of life. You can find so many inspiration from Statistics and Data Analysis for Nursing Research also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Statistics and Data Analysis for Nursing Research book for free.



Statistics for Nursing Research

Statistics for Nursing Research Author Susan K. Grove
ISBN-10 0323358810
Release 2016-02-01
Pages 512
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Understand the statistical methods used in nursing research articles! Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition helps you interpret and analyze the statistical data found in health sciences research articles. Practical exercises show how to critically appraise sampling and measurement techniques, evaluate results, and conduct a power analysis for a study. Written by nursing statistics experts Susan Grove and Daisha Cipher, this is the only statistics workbook for nursing to include research examples from both nursing and medical literature for a complete perspective on health sciences research. Comprehensive coverage includes exercises that address all common techniques of sampling, measurement, and statistical analysis that you are likely to see in nursing and medical literature. A literature-based approach incorporates a relevant research article into each exercise/chapter, with key excerpts. 45 sampling, measurement, and statistical analysis exercises provide a practical review of both basic and advanced techniques, and prepare you to apply statistics to nursing practice. Consistent format for all chapters facilitates quick review and easier learning, covering the statistical technique in review, results from a research article, and study questions. Study questions in each chapter help you apply concepts to clinical practice. Questions to Be Graded in each chapter may be completed and submitted online, to assess your mastery of key statistical techniques. A concise index makes it easy to locate information quickly. NEW examples show the latest, high-quality research studies. NEW! Expanded coverage helps undergraduate students apply the information learned in statistics and research courses, serves as a refresher/review for graduate students, and also helps in critically appraising studies to determine whether their findings may be used in evidence-based practice. NEW! Understanding Statistical Methods section includes exercises to help in understanding the levels of measurement (nominal, ordinal, interval, and ratio) and in appraising the samples and measurement methods in studies. NEW! Conducting and Interpreting Statistical Analyses section includes exercises to help in understanding the power analysis and how to conduct a power analysis for a study, showing how to determine the most appropriate statistical method(s) for analyzing data for a class project, for a clinical agency project, or for an actual research study. NEW! Answers to study questions are located in the back of the book.



Data Analysis Statistics for Nursing Research

Data Analysis   Statistics for Nursing Research Author Denise F. Polit
ISBN-10 0838563295
Release 1996-01
Pages 506
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This introductory textbook uses a conversational style to teach students how to use statistical methods and procedures for the analysis of research findings. Students are guided through the process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to clean data, and how to work around missing data, is discussed.



Graphics for Statistics and Data Analysis with R

Graphics for Statistics and Data Analysis with R Author Kevin J Keen
ISBN-10 9781584880875
Release 2010-04-26
Pages 489
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Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation. The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the quantile-quantile plot. The author discusses nonparametric and parametric density estimation, diagnostic plots for the simple linear regression model, polynomial regression, and locally weighted polynomial regression for producing a smooth curve through data on a scatterplot. The last chapter illustrates visualizing multivariate data with examples using Trellis graphics. Showing how to use graphics to display or summarize data, this text provides best practice guidelines for producing and choosing among graphical displays. It also covers the most effective graphing functions in R. R code is available for download on the book’s website.



Advanced Design in Nursing Research

Advanced Design in Nursing Research Author Pamela J. Brink
ISBN-10 0803958005
Release 1998
Pages 413
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This Second Edition of the bestselling Advanced Design in Nursing Research has been substantially revised and reorganized. Using the principle that the level of knowledge available on a research topic determines the level of design that can be used to study the topic, the contributors present discussions of research at three levels of design: theoretically based experimental designs; comparative and correlated survey designs; and exploratory-descriptive research designs. Strengths and weaknesses of each design in sampling, methods, reliability, validity, data analysis and issues related to human subjects are addressed. Contributors also discuss writing and evaluating proposals.



Nursing Research

Nursing Research Author Denise F. Polit
ISBN-10 0781737338
Release 2004
Pages 758
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This graduate level nursing research textbook continues the expansion of coverage on qualitative research, including important issues for specific qualitative traditions such as grounded theory, phenomenology and ethnography. Developing solid evidence for practice will be emphasized throughout the text, and important evaluative concepts like reliability, validity, and trustworthiness will be introduced. Other new features include stronger international content (with an emphasis on Canadian and Australian research), inclusion of “tips” in boxes located in appropriate places throughout the chapters, and the use of summary bullet points. This edition will now offer a free Connection Website, connection.LWW.com/go/polit.



Nursing Research and Statistics

Nursing Research and Statistics Author Sharma Suresh
ISBN-10 9788131237861
Release 2014-09-08
Pages 534
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Nursing Research and Statistics



Statistics for Evidence Based Practice in Nursing

Statistics for Evidence Based Practice in Nursing Author MyoungJin Kim
ISBN-10 9781284088373
Release 2016-07-22
Pages 414
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Statistics for Evidence-Based Practice in Nursing, Second Edition presents statistics in a readable, user-friendly manner for both graduate students and the professional nurse.



Statistical Methods for Health Care Research

Statistical Methods for Health Care Research Author Barbara Hazard Munro
ISBN-10 0781748402
Release 2005
Pages 494
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Focusing on the statistical methods most frequently used in the health care literature and featuring numerous charts, graphs, and up-to-date examples from the literature, this text provides a thorough foundation for the statistics portion of nursing and all health care research courses. All Fifth Edition chapters include new examples and new computer printouts using the latest software, SPSS for Windows, Version 12. New material on regression diagnostics has been added.



Evidence based Nursing

Evidence based Nursing Author Alba DiCenso
ISBN-10 0323025919
Release 2005
Pages 600
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Accompanying CD-ROM has the full text of the book in electronic format with linking, classification, and coding, with filtering, keyword searching, and the option to rearrange content.



Clinical Research

Clinical Research Author Manfred Stommel
ISBN-10 0781735181
Release 2004
Pages 462
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This unique textbook integrates statistical concepts into evidence-based clinical practice and patient management. Research concepts and techniques are drawn from epidemiology, bio-statistics, and psychometrics, as well as educational and social science research. Clinical examples throughout the text illustrate practical and scientifically sound applications of the concepts. Data tables and research vignettes highlight statistical distributions involving probability. Methods to locate and utilize web-based information relevant to clinical research are discussed, and web URLs are provided. Further learning is encouraged by the inclusion of suggested activities, recommended readings, references, and a comprehensive glossary of research terms. Additional resources are available at a Connection Website, connection.LWW.com/go/stommel.



Statistics for Health Care Research

Statistics for Health Care Research Author Susan K. Grove
ISBN-10 141600226X
Release 2007
Pages 351
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Understanding Social Statistics

Understanding Social Statistics Author Jane Fielding
ISBN-10 9781446228166
Release 2006-01-18
Pages 360
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`This book is highly recommended for libraries and departments to adopt. If I had to teach a statistics class for sociology students this would be a book I would surely choose. The book achieves two very important goals: it teaches students a software package and trains them in the statistical analysis of sociological data' - Journal of Applied Statistics This fully revised, expanded and updated Second Edition of the best-selling textbook by Jane Fielding and Nigel Gilbert provides a comprehensive yet accessible guide to quantitative data analysis. Designed to help take the fear out of the use of numbers in social research, this textbook introduces students to statistics as a powerful means of revealing patterns in human behaviour. The textbook covers everything typically included in an introductory course on social statistics for students in the social sciences and the authors have taken the opportunity of this Second Edition to bring the data sources as current as possible. The book is full of up-to-date examples and useful and clear illustrations using the latest SPSS software. While maintaining the student-friendly elements of the first, such as chapter summaries, exercises at the end of each chapter, and a glossary of key terms, new features to this edition include: - Updated examples and references SPSS coverage and screen-shots now incorporate the current version 14.0 and are used to demonstrate the latest social statistics datasets; - Additions to content include a brand new section on developing a coding frame and an additional discussion of weighting counts as a means of analyzing published statistics; - Enhanced design aids navigation which is further simplified by the addition of core objectives for each chapter and bullet-pointed chapter summaries; - The updated Website at http:/www.soc.surrey.ac.uk/uss/index.html reflects changes made to the text and provides updated datasets; A valuable and practical guide for students dealing with the large amounts of data that are typically collected in social surveys, the Second Edition of Understanding Social Statistics is an essential textbook for courses on statistics and quantitative research across the social sciences.



Clinical Analytics and Data Management for the DNP

Clinical Analytics and Data Management for the DNP Author Martha L. Sylvia, PhD, MBA, RN
ISBN-10 9780826129741
Release 2014-05-05
Pages 240
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"DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars.--Doody's Medical Reviews Strong data management knowledge and skills are a requirement for every DNP. This unique text focuses on fostering the rigorous, meticulous data management skills that can improve care experience, health outcomes, and cost savings worldwide. It provides a knowledge base, describes the regulatory and ethical context, outlines a process to guide evaluation, presents a compendium of resources, and includes examples of evaluation of translation. It takes the DNP student step by step through the complete process of data management, including planning, data collection, data governance and cleansing, analysis, and data presentation. Moreover, the text continues the process of establishing a sturdy clinical data management (CDM) skill base by presenting techniques for ongoing project monitoring after analysis and evaluation are concluded. A progressive case study illustrates multiple techniques throughout each chapter, enabling students to apply what they have learned to their own DNP projects. The book features information from professors who are highly experienced in teaching CDM as well as a renowned scholar of population health analytics. The text provides very specific examples of techniques using SPSSÆ software that is familiar to graduate nursing students. Chapters include objectives, references, and examples from translation projects to assist students to learn and apply chapter content. Appendices describe numerous tools and practical strategies compiled by the authors over several years of teaching CDM to DNP students. Key Features: Meets the specific data management needs of the DNP student from planning to presentation Presents a wide selection of data display options through frequent illustrations of SPSS data Uses a progressive case study to illustrate multiple techniques and methods throughout chapters Provides substantial content necessary for the DNP student to rigorously evaluate DNP innovations/projects Includes very specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students



Statistics in Medicine

Statistics in Medicine Author Robert H. Riffenburgh
ISBN-10 9780123848659
Release 2012-08-13
Pages 738
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Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers. The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method. The text opens with how to plan studies from conception to publication and what to do with your data, and follows with step-by-step instructions for biostatistical methods from the simplest levels (averages, bar charts) progressively to the more sophisticated methods now being seen in medical articles (multiple regression, noninferiority testing). Examples are given from almost every medical specialty and from dentistry, nursing, pharmacy, and health care management. A preliminary guide is given to tailor sections of the text to various lengths of biostatistical courses. User-friendly format includes medical examples, step-by-step methods, and check-yourself exercises appealing to readers with little or no statistical background, across medical and biomedical disciplines Facilitates stand-alone methods rather than a required sequence of reading and references to prior text Covers trial randomization, treatment ethics in medical research, imputation of missing data, evidence-based medical decisions, how to interpret medical articles, noninferiority testing, meta-analysis, screening number needed to treat, and epidemiology Fills the gap left in all other medical statistics books between the reader’s knowledge of how to go about research and the book’s coverage of how to analyze results of that research New in this Edition: New chapters on planning research, managing data and analysis, Bayesian statistics, measuring association and agreement, and questionnaires and surveys New sections on what tests and descriptive statistics to choose, false discovery rate, interim analysis, bootstrapping, Bland-Altman plots, Markov chain Monte Carlo (MCMC), and Deming regression Expanded coverage on probability, statistical methods and tests relatively new to medical research, ROC curves, experimental design, and survival analysis 35 Databases in Excel format used in the book and can be downloaded and transferred into whatever format is needed along with PowerPoint slides of figures, tables, and graphs from the book included on the companion site, http://www.elsevierdirect.com/companion.jsp?ISBN=9780123848642 Medical subject index offers additional search capabilities



Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications Author Robert Nisbet
ISBN-10 9780124166455
Release 2017-11-09
Pages 822
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Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications