Testing Statistical Assumptions In Research
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Testing Statistical Assumptions In Research
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Author : J. P. Verma
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-02
Testing Statistical Assumptions In Research written by J. P. Verma and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-02 with Mathematics categories.
Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met. Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient. An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations Describes different assumptions associated with different statistical tests commonly used by research scholars Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.
Testing Statistical Assumptions In Research
DOWNLOAD
Author : J. P. Verma
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-04
Testing Statistical Assumptions In Research written by J. P. Verma and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-04 with Mathematics categories.
Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met. Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient. An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations Describes different assumptions associated with different statistical tests commonly used by research scholars Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.
Testing Statistical Assumptions In Research
DOWNLOAD
Author : J. P. Verma
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-04
Testing Statistical Assumptions In Research written by J. P. Verma and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-04 with Mathematics categories.
Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met. Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient. An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations Describes different assumptions associated with different statistical tests commonly used by research scholars Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.
Your Statistical Consultant
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Author : Rae R. Newton
language : en
Publisher: SAGE
Release Date : 2013
Your Statistical Consultant written by Rae R. Newton and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Education categories.
How do you bridge the gap between what you learned in your statistics course and the questions you want to answer in your real-world research? Oriented towards distinct questions in a "How do I?" or "When should I?" format, Your Statistical Consultant is the equivalent of the expert colleague down the hall who fields questions about describing, explaining, and making recommendations regarding thorny or confusing statistical issues. The book serves as a compendium of statistical knowledge, both theoretical and applied, that addresses the questions most frequently asked by students, researchers and instructors. Written to be responsive to a wide range of inquiries and levels of expertise, the book is flexibly organized so readers can either read it sequentially or turn directly to the sections that correspond to their concerns.
Sweating The Small Stuff Does Data Cleaning And Testing Of Assumptions Really Matter In The 21st Century
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Author :
language : en
Publisher: Frontiers E-books
Release Date :
Sweating The Small Stuff Does Data Cleaning And Testing Of Assumptions Really Matter In The 21st Century written by and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Evaluating Statistical Validity Of Research Reports
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Author : Amanda L. Golbeck
language : en
Publisher:
Release Date : 1986
Evaluating Statistical Validity Of Research Reports written by Amanda L. Golbeck and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Decision making categories.
Applied Statistics From Bivariate Through Multivariate Techniques
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Author : Rebecca M. Warner
language : en
Publisher: SAGE
Release Date : 2013
Applied Statistics From Bivariate Through Multivariate Techniques written by Rebecca M. Warner and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.
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.
Introduction To Robust Estimation And Hypothesis Testing
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Author : Rand R. Wilcox
language : en
Publisher: Academic Press
Release Date : 2011-12-14
Introduction To Robust Estimation And Hypothesis Testing written by Rand R. Wilcox and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-14 with Mathematics categories.
This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. - Covers latest developments in robust regression - Covers latest improvements in ANOVA - Includes newest rank-based methods - Describes and illustrated easy to use software
Statistical Analysis For Education And Psychology Researchers
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Author : Ian Peers
language : en
Publisher: Routledge
Release Date : 2006-02-27
Statistical Analysis For Education And Psychology Researchers written by Ian Peers and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-27 with Education categories.
Basic statistical concepts such as probability, estimation and inference, and their role in research design and analysis are presented in this volume. The author demonstrates which statistical test to use in given circumstances and how to use it, drawing on data from psychology and education.; Written for those without a strong mathematical background, the book's examples can be worked using a pocket calculator. "Real life" data are analyzed using statistical software (SAS), output is interpreted, and a decision chart is presented which summarizes considerations when choosing a statistical test.
Experimental Research Methods In Language Learning
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Author : Aek Phakiti
language : en
Publisher: Bloomsbury Publishing
Release Date : 2014-12-18
Experimental Research Methods In Language Learning written by Aek Phakiti and has been published by Bloomsbury Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-18 with Language Arts & Disciplines categories.
Language learning research aims to describe and fully explain how and why language learning takes place, but can fall short of its stated purpose. Systematic, rigorous research is needed if the growing field of language learning is to progress methodically. This book demonstrates and fully explains such a methodology. Given that research in language acquisition yields practical pedagogical implications, it is crucial that it is rigorous and accurate. This book offers a quantitative research methodology that relies on statistical analysis in order to make inferences and conclusions about language learning. Experimental research aims to understand differences between or within groups of learners under manipulated environments. It requires strict control of conditions, enabling interpretations with a low factor of error. Aek Phakiti provides step-by-step guidelines and underlying principles, epistemology and methodology, in a book that is essential for advanced students of language acquisition and language and education.