Buy ub-news.com ?
Products related to Inference:
-
Understanding Political Science Research Methods : The Challenge of Inference
This text starts by explaining the fundamental goal of good political science research—the ability to answer interesting and important questions by generating valid inferences about political phenomena.Before the text even discusses the process of developing a research question, the authors introduce the reader to what it means to make an inference and the different challenges that social scientists face when confronting this task.Only with this ultimate goal in mind will students be able to ask appropriate questions, conduct fruitful literature reviews, select and execute the proper research design, and critically evaluate the work of others.The authors' primary goal is to teach students to critically evaluate their own research designs and others’ and analyze the extent to which they overcome the classic challenges to making inference: internal and external validity concerns, omitted variable bias, endogeneity, measurement, sampling, and case selection errors, and poor research questions or theory.As such, students will not only be better able to conduct political science research, but they will also be more savvy consumers of the constant flow of causal assertions that they confront in scholarship, in the media, and in conversations with others. Three themes run through Barakso, Sabet, and Schaffner’s text: minimizing classic research problems to making valid inferences, effective presentation of research results, and the nonlinear nature of the research process.Throughout their academic years and later in their professional careers, students will need to effectively convey various bits of information.Presentation skills gleaned from this text will benefit students for a lifetime, whether they continue in academia or in a professional career.Several distinctive features make this book noteworthy:A common set of examples threaded throughout the text give students a common ground across chapters and expose them to a broad range of subfields in the discipline.Box features throughout the book illustrate the nonlinear, "non-textbook" reality of research, demonstrate the often false inferences and poor social science in the way the popular press covers politics, and encourage students to think about ethical issues at various stages of the research process.
Price: 68.99 £ | Shipping*: 0.00 £ -
Causal Inference for Data Science
When you know the cause of an event, you can affect its outcome.This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning. In Causal Inference for Data Science you will learn how to: Model reality using causal graphsEstimate causal effects using statistical and machine learning techniquesDetermine when to use A/B tests, causal inference, and machine learningExplain and assess objectives, assumptions, risks, and limitationsDetermine if you have enough variables for your analysis It's possible to predict events without knowing what causes them.Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes.Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events.You'll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions.
Price: 45.99 £ | Shipping*: 0.00 £ -
Inference and Learning from Data: Volume 2 : Inference
This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference.This second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning.A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code.Supported by sister volumes Foundations and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.
Price: 74.99 £ | Shipping*: 0.00 £ -
Social Inquiry and Bayesian Inference : Rethinking Qualitative Research
Fairfield and Charman provide a modern, rigorous and intuitive methodology for case-study research to help social scientists and analysts make better inferences from qualitative evidence.The book develops concrete guidelines for conducting inference to best explanation given incomplete information; no previous exposure to Bayesian analysis or specialized mathematical skills are needed.Topics covered include constructing rival hypotheses that are neither too simple nor overly complex, assessing the inferential weight of evidence, counteracting cognitive biases, selecting cases, and iterating between theory development, data collection, and analysis.Extensive worked examples apply Bayesian guidelines, showcasing both exemplars of intuitive Bayesian reasoning and departures from Bayesian principles in published case studies drawn from process-tracing, comparative, and multimethod research.Beyond improving inference and analytic transparency, an overarching goal of this book is to revalue qualitative research and place it on more equal footing with respect to quantitative and experimental traditions by illustrating that Bayesianism provides a universally applicable inferential framework.
Price: 29.99 £ | Shipping*: 0.00 £
Similar search terms for Inference:
-
Statistical Foundations, Reasoning and Inference : For Science and Data Science
This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science.The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty.Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design.The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory.It will also be useful for data science practitioners who want to strengthen their statistics skills.
Price: 99.99 £ | Shipping*: 0.00 £ -
Statistical Inference
This book builds theoretical statistics from the first principles of probability theory.Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts.Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background.It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.
Price: 71.99 £ | Shipping*: 0.00 £ -
Inference and Representation : A Study in Modeling Science
The first comprehensive defense of an inferential conception of scientific representation with applications to art and epistemology. Mauricio Suárez develops a conception of representation that delivers a compelling account of modeling practice.He begins by discussing the history and methodology of model building, charting the emergence of what he calls the modeling attitude, a nineteenth-century and fin de siècle development.Prominent cases of models, both historical and contemporary, are used as benchmarks for the accounts of representation considered throughout the book.After arguing against reductive naturalist theories of scientific representation, Suárez sets out his own account: a case for pluralism regarding the means of representation and minimalism regarding its constituents.He shows that scientists employ a variety of modeling relations in their representational practice—which helps them to assess the accuracy of their representations—while demonstrating that there is nothing metaphysically deep about the constituent relation that encompasses all these diverse means. The book also probes the broad implications of Suárez’s inferential conception outside scientific modeling itself, covering analogies with debates about artistic representation and philosophical thought over the past several decades.
Price: 28.00 £ | Shipping*: 0.00 £ -
Nonparametric Statistical Inference
Praise for previous editions:"… a classic with a long history." – Statistical Papers"The fact that the first edition of this book was published in 1971 … [is] testimony to the book’s success over a long period." – ISI Short Book Reviews"… one of the best books available for a theory course on nonparametric statistics. … very well written and organized … recommended for teachers and graduate students." – Biometrics"… There is no competitor for this book and its comprehensive development and application of nonparametric methods.Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics"… Useful to students and research workers … a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical AssociationSince its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametrics.The Sixth Edition carries on this tradition and incorporates computer solutions based on R.Features Covers the most commonly used nonparametric procedures States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences Presents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures Includes an Appendix of user-friendly tables needed for solutions to all data-oriented examples Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS Lists over 100 new referencesNonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly.All of the R solutions are new and make this book much more useful for applications in modern times.It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers.
Price: 105.00 £ | Shipping*: 0.00 £
* All prices are inclusive of VAT and, if applicable, plus shipping costs. The offer information is based on the details provided by the respective shop and is updated through automated processes. Real-time updates do not occur, so deviations can occur in individual cases.