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| Author | : Lyle F. Bachman |
| Publisher | : Cambridge University Press |
| Total Pages | : 382 |
| Release | : 2004-11-18 |
| Genre | : Foreign Language Study |
| ISBN | : 0521802776 |
This book provides language teachers with guidelines to develop suitable listening tests.
| Author | : R. Green |
| Publisher | : Springer |
| Total Pages | : 369 |
| Release | : 2013-04-08 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 1137018291 |
Provides a step-by-step approach to the most useful statistical analyses for language test developers and researchers using IBM SPSS, Winsteps and Facets. It contains clearly-worked out examples for each analysis with detailed explanations.
| Author | : Lyle F. Bachman |
| Publisher | : Cambridge University Press |
| Total Pages | : 0 |
| Release | : 2004-11-18 |
| Genre | : Foreign Language Study |
| ISBN | : 9780521003285 |
Statistical Analyses for Language Assessment enables practitioners to apply statistics effectively to the development and use of language assessments. The Workbook and CD contain datasets from actual language assessments and data analysis exercises.
| Author | : Lyle Bachman |
| Publisher | : Cambridge University Press |
| Total Pages | : 182 |
| Release | : 2005-04-07 |
| Genre | : Foreign Language Study |
| ISBN | : 9780521609067 |
This book enables practitioners to apply statistics effectively to the development and use of language assessments. This is a Workbook and CD ROM pack which will support the main text. Each chapter will offer activities to parallel the chapters in the book. The activities are intended to provide readers with opportunities to work with and apply the concepts and procedures presented, using datasets from language assessment research.
| Author | : Rotem Dror |
| Publisher | : Springer Nature |
| Total Pages | : 98 |
| Release | : 2022-06-01 |
| Genre | : Computers |
| ISBN | : 3031021746 |
Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental. The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.
| Author | : James Dean Brown |
| Publisher | : |
| Total Pages | : |
| Release | : 2016-08-25 |
| Genre | : |
| ISBN | : 9781537312866 |
James Dean Brown ("JD"), currently Professor of Second Language Studies at the University of Hawaii at Manoa, has lectured and taught around the world and has published numerous articles and books on language testing, curriculum design, research methods, and connected speech. For close to twenty years, Professor Brown has contributed a regular column called Statistics Corner to Shiken, the biannual publication of the Testing and Evaluation Special Interest Group (TEVAL) of the Japan Association for Language Teaching (JALT). In his column, JD answers questions submitted by readers about language testing and statistics in an informal and easy to understand format. This volume brings together in one convenient location, forty-one Statistics Corner columns-updated, arranged thematically, and fully indexed. Presented in a question and answer format, the clear and concise explanations are both accessible to novices and engaging to experts. Topics addressed include: Second language testing strategies Likert items and scales of measurement Validity and reliability of tests and questionnaires Item analysis techniques for norm-referenced and criterion-referenced tests Conducting and interpreting principle component and factor analyses Planning and interpreting qualitative, quantitative, and mixed-methods research Clear explanations of the meaning and interpretation of frequently reported statistics such as Cronbach's alpha, standard error, confidence intervals, eta squared, Cohen's Kappa, skewness and kurtosis, and more."
| Author | : J. P. Verma |
| Publisher | : John Wiley & Sons |
| Total Pages | : 224 |
| Release | : 2019-04-02 |
| Genre | : Mathematics |
| ISBN | : 1119528410 |
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.
| Author | : Vahid Aryadoust |
| Publisher | : Routledge |
| Total Pages | : 303 |
| Release | : 2019-03-27 |
| Genre | : Education |
| ISBN | : 1351741225 |
Quantitative Data Analysis for Language Assessment Volume I: Fundamental Techniques is a resource book that presents the most fundamental techniques of quantitative data analysis in the field of language assessment. Each chapter provides an accessible explanation of the selected technique, a review of language assessment studies that have used the technique, and finally, an example of an authentic study that uses the technique. Readers also get a taste of how to apply each technique through the help of supplementary online resources that include sample data sets and guided instructions. Language assessment students, test designers, and researchers should find this a unique reference as it consolidates theory and application of quantitative data analysis in language assessment.
| Author | : James Dean Brown |
| Publisher | : Cambridge University Press |
| Total Pages | : 640 |
| Release | : 2002-05-20 |
| Genre | : Foreign Language Study |
| ISBN | : 0521000831 |
Criterion-referenced Language Testing looks at the practical applications of this new area of language testing.
| Author | : Nikos Ntoumanis |
| Publisher | : John Wiley & Sons |
| Total Pages | : 312 |
| Release | : 2016-01-19 |
| Genre | : Medical |
| ISBN | : 1118962052 |
"Ntoumanis and Myers have done sport and exercise science researchers and students a tremendous service in producing An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists. This book has an outstanding compilation of comprehensible chapters dealing with the important concepts and technical minutia of the statistical analyses that sport and exercise science scholars use (or should be using!) in their efforts to conduct meaningful research in the field. It is a resource that all sport and exercise scientists and their students should have on their book shelves." —Robert Eklund, School of Sport, University of Stirling, UK "Motivating, to have a statistics text devoted to enabling researchers studying sport and exercise science to apply the most sophisticated analytical techniques to their data. Authors hit the mark between using technical language as necessary and user-friendly terms or translations to keep users encouraged. Text covers traditional and well-used tools but also less common and more complex tools, but always with familiar examples to make their explanations come alive. As a dynamic systems theorist and developmentalist, I would love to see more researchers in my area create study designs that would enable the use of tools outlined here, such as multilevel structural equation modeling (MSEM) or mediation & moderation analyses, to uncover cascades of relations among subsystems contributing to motor performance, over time. This text can facilitate that outcome." —Beverly D. Ulrich, School of Kinesiology, University of Michigan, USA "The domain of quantitative methods is constantly evolving and expanding. This means that there is tremendous pressure on researchers to stay current, both in terms of best practices and improvements in more traditional methods as well as increasingly complex new methods. With this volume Ntoumanis and Myers present a nice cross-section of both, helping sport and exercise science researchers to address old questions in better ways, and, even more excitingly, to address new questions entirely. I have no doubt that this volume will quickly become a lovingly dog-eared companion for students and researchers, helping them to continue to move the field forward." —Gregory R. Hancock, University of Maryland and Center for Integrated Latent Variable Research (CILVR), USA
