Author: Roy Sabo
Publisher: Springer Science & Business Media
ISBN: 1461487080
Category : Medical
Languages : en
Pages : 218
Book Description
This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, describe the entire data analysis process from hypothesis generation to writing the results in a manuscript. Chapters cover, among other topics: one and two-sample proportions, multi-category data, one and two-sample means, analysis of variance, and regression. Throughout the text, the authors explain statistical procedures and concepts using a non-statistical language. This accessible approach is complete with real-world examples and sample write-ups for the Methods and Results sections of scholarly papers. The text also allows for the concurrent use of the programming language R, which is an open-source program created, maintained and updated by the statistical community. R is freely available and easy to download.
Statistical Research Methods
Author: Roy Sabo
Publisher: Springer Science & Business Media
ISBN: 1461487080
Category : Medical
Languages : en
Pages : 218
Book Description
This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, describe the entire data analysis process from hypothesis generation to writing the results in a manuscript. Chapters cover, among other topics: one and two-sample proportions, multi-category data, one and two-sample means, analysis of variance, and regression. Throughout the text, the authors explain statistical procedures and concepts using a non-statistical language. This accessible approach is complete with real-world examples and sample write-ups for the Methods and Results sections of scholarly papers. The text also allows for the concurrent use of the programming language R, which is an open-source program created, maintained and updated by the statistical community. R is freely available and easy to download.
Publisher: Springer Science & Business Media
ISBN: 1461487080
Category : Medical
Languages : en
Pages : 218
Book Description
This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, describe the entire data analysis process from hypothesis generation to writing the results in a manuscript. Chapters cover, among other topics: one and two-sample proportions, multi-category data, one and two-sample means, analysis of variance, and regression. Throughout the text, the authors explain statistical procedures and concepts using a non-statistical language. This accessible approach is complete with real-world examples and sample write-ups for the Methods and Results sections of scholarly papers. The text also allows for the concurrent use of the programming language R, which is an open-source program created, maintained and updated by the statistical community. R is freely available and easy to download.
Journal of Statistical Research
Author:
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 476
Book Description
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 476
Book Description
An Introduction to Statistical Analysis in Research
Author: Kathleen F. Weaver
Publisher: John Wiley & Sons
ISBN: 1119299683
Category : Mathematics
Languages : en
Pages : 608
Book Description
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 journal articles and a member of the American Statistical Association, she received her PhD in Anthropology from the University of Tennessee. PABLO F. WEAVER, PhD, is Instructor in the Department of Biology at the University of La Verne. The author of numerous journal articles, he received his PhD in Ecology and Evolutionary Biology from the University of Colorado.
Publisher: John Wiley & Sons
ISBN: 1119299683
Category : Mathematics
Languages : en
Pages : 608
Book Description
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 journal articles and a member of the American Statistical Association, she received her PhD in Anthropology from the University of Tennessee. PABLO F. WEAVER, PhD, is Instructor in the Department of Biology at the University of La Verne. The author of numerous journal articles, he received his PhD in Ecology and Evolutionary Biology from the University of Colorado.
Quantitative and Statistical Research Methods
Author: William E. Martin
Publisher: John Wiley & Sons
ISBN: 111823457X
Category : Social Science
Languages : en
Pages : 498
Book Description
Quantitative and Statistical Research Methods This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles. Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to: Pinpoint research questions and hypotheses Identify, classify, and operationally define the study variables Choose appropriate research designs Conduct power analysis Select an appropriate statistic for the problem Use a data set Conduct data screening and analyses using SPSS Interpret the statistics Write the results related to the problem Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects.
Publisher: John Wiley & Sons
ISBN: 111823457X
Category : Social Science
Languages : en
Pages : 498
Book Description
Quantitative and Statistical Research Methods This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles. Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to: Pinpoint research questions and hypotheses Identify, classify, and operationally define the study variables Choose appropriate research designs Conduct power analysis Select an appropriate statistic for the problem Use a data set Conduct data screening and analyses using SPSS Interpret the statistics Write the results related to the problem Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects.
Adaptive Survey Design
Author: Barry Schouten
Publisher: CRC Press
ISBN: 1498767885
Category : Mathematics
Languages : en
Pages : 267
Book Description
Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members, often for cost and bias reduction. People vary in how likely they are to respond and in how they respond. This variation leads to opportunities to selectively deploy design features in order to control both nonresponse and measurement errors. ASD aims at the optimal matching of design features and the characteristics of respondents given the survey budget. Such a goal is sensible, but ASD requires investment in more advanced technical systems and management infrastructure and asks for the collection of relevant auxiliary data. So what are current best practices in ASD? And is ASD worthwhile when the same auxiliary data are employed in the estimation afterwards? In this book, the authors provide answers to these questions, and much more.
Publisher: CRC Press
ISBN: 1498767885
Category : Mathematics
Languages : en
Pages : 267
Book Description
Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members, often for cost and bias reduction. People vary in how likely they are to respond and in how they respond. This variation leads to opportunities to selectively deploy design features in order to control both nonresponse and measurement errors. ASD aims at the optimal matching of design features and the characteristics of respondents given the survey budget. Such a goal is sensible, but ASD requires investment in more advanced technical systems and management infrastructure and asks for the collection of relevant auxiliary data. So what are current best practices in ASD? And is ASD worthwhile when the same auxiliary data are employed in the estimation afterwards? In this book, the authors provide answers to these questions, and much more.
Statistical Strategies for Small Sample Research
Author: Rick H. Hoyle
Publisher: SAGE Publications
ISBN: 1506320082
Category : Social Science
Languages : en
Pages : 394
Book Description
Newer statistical models, such as structural equation modeling and hierarchical linear modeling, require large sample sizes inappropriate for many research questions or unrealistic for many research arenas. How can researchers get the sophistication and flexibility of large sample studies without the requirement of prohibitively large samples? This book describes and illustrates statistical strategies that meet the sophistication/flexibility criteria for analyzing data from small samples of fewer than 150 cases. Contributions from some of the leading researchers in the field cover the use of multiple imputation software and how it can be used profitably with small data sets and missing data; ways to increase statistical power when sample size cannot be increased; and strategies for computing effect sizes and combining effect sizes across studies. Other contributions describe how to hypothesis test using the bootstrap; methods for pooling effect size indicators from single-case studies; frameworks for drawing inferences from cross-tabulated data; how to determine whether a correlation or covariance matrix warrants structure analysis; and what conditions indicate latent variable modeling is a viable approach to correct for unreliability in the mediator. Other topics include the use of dynamic factor analysis to model temporal processes by analyzing multivariate; time-series data from small numbers of individuals; techniques for coping with estimation problems in confirmatory factor analysis in small samples; how the state space model can be used with surprising accuracy with small data samples; and the use of partial least squares as a viable alternative to covariance-based SEM when the N is small and/or the number of variables in a model is large.
Publisher: SAGE Publications
ISBN: 1506320082
Category : Social Science
Languages : en
Pages : 394
Book Description
Newer statistical models, such as structural equation modeling and hierarchical linear modeling, require large sample sizes inappropriate for many research questions or unrealistic for many research arenas. How can researchers get the sophistication and flexibility of large sample studies without the requirement of prohibitively large samples? This book describes and illustrates statistical strategies that meet the sophistication/flexibility criteria for analyzing data from small samples of fewer than 150 cases. Contributions from some of the leading researchers in the field cover the use of multiple imputation software and how it can be used profitably with small data sets and missing data; ways to increase statistical power when sample size cannot be increased; and strategies for computing effect sizes and combining effect sizes across studies. Other contributions describe how to hypothesis test using the bootstrap; methods for pooling effect size indicators from single-case studies; frameworks for drawing inferences from cross-tabulated data; how to determine whether a correlation or covariance matrix warrants structure analysis; and what conditions indicate latent variable modeling is a viable approach to correct for unreliability in the mediator. Other topics include the use of dynamic factor analysis to model temporal processes by analyzing multivariate; time-series data from small numbers of individuals; techniques for coping with estimation problems in confirmatory factor analysis in small samples; how the state space model can be used with surprising accuracy with small data samples; and the use of partial least squares as a viable alternative to covariance-based SEM when the N is small and/or the number of variables in a model is large.
Research Design & Statistical Analysis
Author: Arnold D. Well
Publisher: Psychology Press
ISBN: 1135641080
Category : Mathematics
Languages : en
Pages : 871
Book Description
"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover
Publisher: Psychology Press
ISBN: 1135641080
Category : Mathematics
Languages : en
Pages : 871
Book Description
"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover
Breakthroughs in Statistics
Author: Samuel Kotz
Publisher: Springer Science & Business Media
ISBN: 1461206677
Category : Mathematics
Languages : en
Pages : 576
Book Description
Volume III includes more selections of articles that have initiated fundamental changes in statistical methodology. It contains articles published before 1980 that were overlooked in the previous two volumes plus articles from the 1980's - all of them chosen after consulting many of today's leading statisticians.
Publisher: Springer Science & Business Media
ISBN: 1461206677
Category : Mathematics
Languages : en
Pages : 576
Book Description
Volume III includes more selections of articles that have initiated fundamental changes in statistical methodology. It contains articles published before 1980 that were overlooked in the previous two volumes plus articles from the 1980's - all of them chosen after consulting many of today's leading statisticians.
Statistical Methods For Research Workers
Author: R a Fisher
Publisher: Gyan Books
ISBN: 9789351286578
Category :
Languages : en
Pages : 407
Book Description
The Title 'Encyclopaedia of Dalits in India (Women) written/authored/edited by Sanjay Paswan, Paramanshi Jaideva', published in the year 2002. The ISBN 9788178350325 is assigned to the Hardcover version of this title. This book has total of pp. 415 (Pages). The publisher of this title is Kalpaz Publications. This Book is in English. The subject of this book is Reference / Dictionary / Encyclopaedia / Scheduled Castes / OBC / Minorities / Sociology. Size of the book is.
Publisher: Gyan Books
ISBN: 9789351286578
Category :
Languages : en
Pages : 407
Book Description
The Title 'Encyclopaedia of Dalits in India (Women) written/authored/edited by Sanjay Paswan, Paramanshi Jaideva', published in the year 2002. The ISBN 9788178350325 is assigned to the Hardcover version of this title. This book has total of pp. 415 (Pages). The publisher of this title is Kalpaz Publications. This Book is in English. The subject of this book is Reference / Dictionary / Encyclopaedia / Scheduled Castes / OBC / Minorities / Sociology. Size of the book is.
Statistics for Research
Author: George Argyrous
Publisher: SAGE
ISBN: 1446210251
Category : Reference
Languages : en
Pages : 609
Book Description
This fully updated edition of Statistics for Research explains statistical concepts in a straight-forward and accessible way using practical examples from a variety of disciplines. If you′re looking for an easy-to-read, comprehensive introduction to statistics with a guide to SPSS, this is the book for you! The new edition features: - Clear explanations of all the main techniques of statistical analysis - A brand new student-friendly, easy-to-navigate design - Even more step-by-step screenshots of SPSS commands and outputs - An extensive glossary of terms, ideal for those new to statistics - End of chapter exercises to help you put your learning into practice - A new, fully updated companion website (www.uk.sagepub.com/argyrous3) with comprehensive student and lecturer resources including additional, discipline specific examples and online readings and WebCT/Blackboard quizzes. This is the ideal textbook for any course in statistical methods across the health and social sciences and a perfect starter book for students, researchers and professionals alike.
Publisher: SAGE
ISBN: 1446210251
Category : Reference
Languages : en
Pages : 609
Book Description
This fully updated edition of Statistics for Research explains statistical concepts in a straight-forward and accessible way using practical examples from a variety of disciplines. If you′re looking for an easy-to-read, comprehensive introduction to statistics with a guide to SPSS, this is the book for you! The new edition features: - Clear explanations of all the main techniques of statistical analysis - A brand new student-friendly, easy-to-navigate design - Even more step-by-step screenshots of SPSS commands and outputs - An extensive glossary of terms, ideal for those new to statistics - End of chapter exercises to help you put your learning into practice - A new, fully updated companion website (www.uk.sagepub.com/argyrous3) with comprehensive student and lecturer resources including additional, discipline specific examples and online readings and WebCT/Blackboard quizzes. This is the ideal textbook for any course in statistical methods across the health and social sciences and a perfect starter book for students, researchers and professionals alike.