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Author: Stefan Riezler Publisher: Springer Nature ISBN: 3031021835 Category : Computers Languages : en Pages : 147
Book Description
Empirical methods are means to answering methodological questions of empirical sciences by statistical techniques. The methodological questions addressed in this book include the problems of validity, reliability, and significance. In the case of machine learning, these correspond to the questions of whether a model predicts what it purports to predict, whether a model's performance is consistent across replications, and whether a performance difference between two models is due to chance, respectively. The goal of this book is to answer these questions by concrete statistical tests that can be applied to assess validity, reliability, and significance of data annotation and machine learning prediction in the fields of NLP and data science. Our focus is on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs). Based on the interpretable parameters of the trained GAMs or LMEMs, the book presents model-based statistical tests such as a validity test that allows detecting circular features that circumvent learning. Furthermore, the book discusses a reliability coefficient using variance decomposition based on random effect parameters of LMEMs. Last, a significance test based on the likelihood ratio of nested LMEMs trained on the performance scores of two machine learning models is shown to naturally allow the inclusion of variations in meta-parameter settings into hypothesis testing, and further facilitates a refined system comparison conditional on properties of input data. This book can be used as an introduction to empirical methods for machine learning in general, with a special focus on applications in NLP and data science. The book is self-contained, with an appendix on the mathematical background on GAMs and LMEMs, and with an accompanying webpage including R code to replicate experiments presented in the book.
Author: Stefan Riezler Publisher: Springer Nature ISBN: 3031021835 Category : Computers Languages : en Pages : 147
Book Description
Empirical methods are means to answering methodological questions of empirical sciences by statistical techniques. The methodological questions addressed in this book include the problems of validity, reliability, and significance. In the case of machine learning, these correspond to the questions of whether a model predicts what it purports to predict, whether a model's performance is consistent across replications, and whether a performance difference between two models is due to chance, respectively. The goal of this book is to answer these questions by concrete statistical tests that can be applied to assess validity, reliability, and significance of data annotation and machine learning prediction in the fields of NLP and data science. Our focus is on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs). Based on the interpretable parameters of the trained GAMs or LMEMs, the book presents model-based statistical tests such as a validity test that allows detecting circular features that circumvent learning. Furthermore, the book discusses a reliability coefficient using variance decomposition based on random effect parameters of LMEMs. Last, a significance test based on the likelihood ratio of nested LMEMs trained on the performance scores of two machine learning models is shown to naturally allow the inclusion of variations in meta-parameter settings into hypothesis testing, and further facilitates a refined system comparison conditional on properties of input data. This book can be used as an introduction to empirical methods for machine learning in general, with a special focus on applications in NLP and data science. The book is self-contained, with an appendix on the mathematical background on GAMs and LMEMs, and with an accompanying webpage including R code to replicate experiments presented in the book.
Author: Brenda Marshall, EdD, PMHNP-BC, ANEF Publisher: Springer Publishing Company ISBN: 0826146376 Category : Medical Languages : en Pages : 258
Book Description
While often greeted with trepidation, the importance of a research project—how it is conducted and its significance to practice—is an essential aspect of nursing and other healthcare arenas. This innovative resource is a user-friendly introduction to evidence-based practice and other types of research-based initiatives that improve patient outcomes. Using a method formed through years of teaching experience, Brenda Marshall translates the difficult and sometimes confusing language of research into everyday vocabulary, linking complicated concepts with easily understood scenarios. Written in quick-access Fast Facts style, this book presents knowledge in a consistent, step-by-step format characterized by bite-sized information. Each chapter opens with learning objectives that unfold into new concepts, followed by everyday life examples. Fast Facts boxes, systematized tables, and new vocabulary reinforce learning and highlight key concepts. This application-based approach helps students question their preconceived notions about research and then engage in it with newfound confidence. Key Features: Translates complex research concepts into straightforward language Demonstrates clear, step-by-step methods that facilitate successful attainment of research goals Helps students to construct an argument, build a theory, and critically explore a belief Promotes self-sufficiency in lifelong learning and achievement Written by an instructor whose classes have propelled many successful research careers
Author: John C. Reinard Publisher: SAGE Publications ISBN: 1506320481 Category : Language Arts & Disciplines Languages : en Pages : 604
Book Description
"While most books on statistics seem to be written as though targeting other statistics professors, John Reinard′s Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done!" --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. Key Features: Emphasizes basic and introductory statistical thinking: The basic needs of novice researchers and students are addressed, while underscoring the foundational elements of statistical analyses in research. Students learn how statistics are used to provide evidence for research arguments and how to evaluate such evidence for themselves. Prepares students to use statistics: Students are encouraged to use statistics as they encounter and evaluate quantitative research. The book details how statistics can be understood by developing actual skills to carry out rudimentary work. Examples are drawn from mass communication, speech communication, and communication disorders. Incorporates SPSS 12 and Excel: A distinguishing feature is the inclusion of coverage of data analysis by use of SPSS 12 and by Excel. Information on the use of major computer software is designed to let students use such tools immediately. Companion Web Site! A dedicated Web site includes a glossary, data sets, chapter summaries, additional readings, links to other useful sites, selected "calculators" for computation of related statistics, additional macros for selected statistics using Excel and SPSS, and extra chapters on multiple discriminant analysis and loglinear analysis. Intended Audience: Ideal for undergraduate and graduate courses in Communication Research Statistics or Methods; also relevant for many Research Methods courses across the social sciences
Author: Publisher: SAGE ISBN: 9780761965176 Category : Business & Economics Languages : en Pages : 446
Book Description
Doing Management Research, a major new textbook, provides answers to questions and problems which researchers invariably encounter when embarking on management research, be it quantitative or qualitative. This book will carefully guide the reader through the research process from beginning to end. An excellent tool for academics and students, it enables the reader to acquire and build upon empirical evidence, and to decide what tools to use to understand and describe what is being observed, and then, which methods of analysis to adopt. There is an entire section dedicated to writing up and communicating the research findings. Written in an accessible and easy-to-use style, this book can be read from cover to cover or dipped
Author: Jerome Kirk Publisher: SAGE ISBN: 9780803924703 Category : Social Science Languages : en Pages : 92
Book Description
Qualitative research is a sociological and anthropological tradition of inquiry. Most critically, qualitative research involves sustained interaction with the people being studied in their own language, and on their own turf. To see qualitative research as strictly disengaged from any form of counting is to miss the point that its basic strategy depends on the reconciliation of diverse research tactics. It is our view that qualitative research can be performed as social science. Understanding the workings of a scientific endeavor, whether it is of the natural or social variety, entails an appreciation of its objectivity. By this convention, the objectivity of a piece of qualitative research is evaluated in terms of the reliability and validity of its observations - the two concepts to which this monograph is devoted.
Author: Catherine S. Taylor Publisher: Oxford University Press ISBN: 0199359245 Category : Psychology Languages : en Pages : 217
Book Description
The Understanding Research series focuses on the process of writing up social research. The series is broken down into three categories: Understanding Statistics, Understanding Measurement, and Understanding Qualitative Research. The books provide researchers with guides to understanding, writing, and evaluating social research. Each volume demonstrates how research should be represented, including how to write up the methodology as well as the research findings. Each volume also reviews how to appropriately evaluate published research. Validity and Validation is an introduction to validity theory and to the methods used to obtain evidence for the validity of research and assessment results. The book pulls together the best thinking from educational and psychological research and assessment over the past 50 years. It briefly describes validity theory's roots in the philosophy of science. It highlights the ways these philosophical perspectives influence concepts of internal and external validity in research methodology, as well as concepts of validity and reliability in educational and psychological tests and measurements. Each chapter provides multiple examples (e.g., research designs and examples of output) to help the readers see how validation work is done in practice, from the ways we design research studies to the ways we interpret research results. Of particular importance is the practical focus on validation of scores from tests and other measures. The book also addresses strategies for investigating the validity of inferences we make about examinees using scores from assessments, as well as how to investigate score uses, the value implications of score interpretations, and the social consequences of score use. With this foundation, the book presents strategies for minimizing threats for validity as well as quantitative and qualitative methods for gathering evidence for the validity of scores.
Author: Neil J. Salkind Publisher: SAGE ISBN: 1412961270 Category : Philosophy Languages : en Pages : 1779
Book Description
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
Author: Hans Wagemaker Publisher: Springer Nature ISBN: 3030530817 Category : Education Languages : en Pages : 279
Book Description
This open access book describes and reviews the development of the quality control mechanisms and methodologies associated with IEA’s extensive program of educational research. A group of renowned international researchers, directly involved in the design and execution of IEA’s international large-scale assessments (ILSAs), describe the operational and quality control procedures that are employed to address the challenges associated with providing high-quality, comparable data. Throughout the now considerable history of IEA’s international large-scale assessments, establishing the quality of the data has been paramount. Research in the complex multinational context in which IEA studies operate imposes significant burdens and challenges in terms of the methodologies and technologies that have been developed to achieve the stated study goals. The demands of the twin imperatives of validity and reliability must be satisfied in the context of multiple and diverse cultures, languages, orthographies, educational structures, educational histories, and traditions. Readers will learn about IEA’s approach to such challenges, and the methods used to ensure that the quality of the data provided to policymakers and researchers can be trusted. An often neglected area of investigation, namely the consequential validity of ILSAs, is also explored, examining issues related to reporting, dissemination, and impact, including discussion of the limits of interpretation. The final chapters address the question of the influence of ILSAs on policy and reform in education, including a case study from Singapore, a country known for its outstanding levels of achievement, but which nevertheless seeks the means of continual improvement, illustrating best practice use of ILSA data.
Author: Stefan Riezler
Author: Stefan Riezler
Author: Brenda Marshall, EdD, PMHNP-BC, ANEF
Author: Stefan Riezler
Author: John C. Reinard
Author: 
Author: Jerome Kirk
Author: Catherine S. Taylor
Author: Marc D. Gellman
Author: Neil J. Salkind
Author: Hans Wagemaker