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visión de conjunto:Críticas This is a very useful book that graduate students should read to help them understand and use their statistical tools. And not just grad students could stand to read it--some of the issues raised such as statistical significance and size effects plague the vast majority of social research. As editor of Social Problems I very frequently came across sophisticated papers that simply reported the statistical significance of findings without saying a word about the magnitude of the effect purportedly being examined or the importance or impact of the phenomenon under discussion.--James A. Holstein Department of Social and Cultural Sciences Marquette UniversityThis book would be suited for professional and/or class use. The benefit for professional use is the vast number of resources and references cited throughout. This wealth of seminal works from some of the best minds in the field of statistics would provide professionals with supplemental knowledge and information on many crucial statistical issues that have recently been proposed debated challenged and mandated (APA).--Victoria Rodlin Statistical Consultant (former faculty Department of Psychology California State University Fullerton)This book will encourage both students and experienced researchers to 'think through' the process critically examine their hypotheses and choose the statistical method best suited to their theory. Thompson's repeated emphasis regarding the importance of interpreting an analysis by comparing results with those across prior related studies is vital and well stated throughout.--Victoria Rodlin Statistical Consultant (former faculty Department of Psychology California State University Fullerton)I mainly teach statistics to nursing students and I could easily see myself switching to Thompson’s book because it is basically one of the most readable serious statistics books I have seen. This is a book that deals with univariate and bivariate statistics and those multivariate statistics where there’s only a single dependent variable. It emphasizes the general linear model as a unifying concept as well as emphasizing effect sizes and confidence intervals in addition to null hypothesis statistical testing.--Kenneth A. Wallston School of Nursing Vanderbilt UniversityThere are a lot of quite simple introductory statistics texts out there ('too cold!') and a large number of really comprehensive ones perhaps best digested over two semesters ('too hot!'). However I found Thompson’s treatment and coverage to be 'just right.' I especially appreciated his conservatism in using and interpreting statistics.--Bruce Thyer College of Social Work Florida State UniversityAn important contribution to improving data analysis and interpretation methods in the social sciences. This book treats many important topics that are ignored in most statistics books. Examples include the limitations of statistical significance tests the importance of effect size indices the important role of distribution shapes in determining ceilings on linear relationships problems of capitalization on sampling error in stepwise regression and many many others. The Statistical Significance chapter is excellent and one of the crown jewels of this book. This is the kind of understanding of significance testing that we should seek to impart to students and researchers. No other stat book to my knowledge has a chapter like this one. This is the direction in which things are moving today.--Frank L. Schmidt College of Business University of IowaA nice contribution to the field providing a gentle introduction to statistics and simultaneously introducing the student to some important advances. The writing which includes plenty of examples from a broad range of applications is accessible to the beginning graduate student and is entertaining to boot. The tables and figures are clear and provide a nice complement to the narrative.--Jeffrey D. Kromrey Department of Educational Measurement and Research University of South FloridaThis is a very well-thought-out book. It is not the same old inferential statistics. It has some snap to it. The author takes on thorny issues that often are not addressed in introductory texts. It is very conceptual and would be appropriate for a number of undergraduate or graduate courses in statistics for students without much in the way of math backgrounds which is to say most of the social behavioral and biomedical areas.--Paul R. Swank Department of Pediatrics University of Texas Health Science Center at HoustonThe exercises in a conceptual book like this should be reflective and thought provoking rather than computational/m-/just like these were done!--Paul R. Swank Department of Pediatrics University of Texas Health Science Center at HoustonThis is an outstanding text that represents a new era in the learning and reporting of statistics in the behavioral sciences. Thompson focuses on analytic thinking rather than mathematical number-crunching unlike others who emphasize calculations at the expense of critical thinking. The use of humor throughout the book is also a distinctive feature and it brings a considerable amount of 'realism' to the text. This book is at the leading edge of methodological advances regarding the interpretation of research outcomes and will serve a critical role in the continued evolution of the behavioral statistics field.--Robin K. Henson Department of Technology and Cognition University of North TexasThe Reflection Problems are an outstanding extension that most other statistics texts do not have.--Robin K. Henson Department of Technology and Cognition University of North Texas This is the best book for graduate students in statistics due to the clarity and simplicity of the exposition.--Pedro Reyes PhD Department of Educational Administration University of Texas at Austin This is the best book for graduate students in statistics due to the clarity and simplicity of the exposition.--Pedro Reyes PhD Department of Educational Administration University of Texas at Austin This text has a clear and logical approach that allows its use across a variety of fields and levels of instruction.--Kirk E. Wheeler PhD Adjunct Lecturer Indiana University School of NursingThompson is an expert at presenting outcomes on a level that challenges students to question how and why and sometimes forces them to abandon their math anxiety and look at numeric outcomes in new ways. For example one student in an 'aha moment' exclaimed 'I just figured out what the standard error is.' That's big!--Gail Delicio E.T. Moore School of Education Clemson University I found the book very useful as an instructor and the students really enjoyed the straightforward approach to explaining statistical methods. The accessible style made it easy for students to grasp and apply statistical concepts.--Tammy Kolbe Department of Education Policy and Leadership University of Maryland-College Park Reseña del editor With humor extraordinary clarity and carefully paced explanations and examples Bruce Thompson shows readers how to use the latest techniques for interpreting research outcomes as well as how to make statistical decisions that result in better research. Utilizing the general linear model to demonstrate how different statistical methods are related to each other Thompson integrates a broad array of methods involving only a single dependent variable ranging from classical and robust location descriptive statistics through effect sizes and on through ANOVA multiple regression loglinear analysis and logistic regression. Special features include SPSS and Excel demonstrations that offer opportunities in the book’s datasets and on Thompson’s website for further exploration of statistical dynamics. Biografía del autor Bruce Thompson is Distinguished Professor of Educational Psychology and Distinguished Professor of Library Sciences Texas A&M University and Adjunct Professor of Family and Community Medicine Baylor College of Medicine Houston. He is the coeditor of the teaching learning and human development section of the American Educational Research Journal and past editor of Educational and Psychological Measurement the series Advances in Social Science Methodology and two other journals. He is the author or editor of 10 books has written over 175 research articles and has made contributions that have been influential in promoting greater emphasis on effect size reporting and interpretation and improved understanding of score reliability.