Statistics As Principled Argument

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Statistics As Principled Argument

Robert P. Abelson
Statistics As Principled Argument Book PDF

Author : Robert P. Abelson
Publisher : Psychology Press
Page : 242 pages
File Size : 53,9 Mb
Release : 2012-09-10
Category : Psychology
ISBN : 9781135694418

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Statistics As Principled Argument by Robert P. Abelson Pdf

In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.

Statistics as Principled Argument

Robert P. Abelson
Statistics as Principled Argument Book PDF

Author : Robert P. Abelson
Publisher : Psychology Press
Page : 242 pages
File Size : 44,6 Mb
Release : 1995
Category : Mathematics
ISBN : 9780805805277

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Statistics as Principled Argument by Robert P. Abelson Pdf

In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.

All of Statistics

Larry Wasserman
All of Statistics Book PDF

Author : Larry Wasserman
Publisher : Springer Science & Business Media
Page : 446 pages
File Size : 52,5 Mb
Release : 2013-12-11
Category : Mathematics
ISBN : 9780387217369

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All of Statistics by Larry Wasserman Pdf

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Statistics As Principled Argument

Robert P. Abelson
Statistics As Principled Argument Book PDF

Author : Robert P. Abelson
Publisher : Psychology Press
Page : 240 pages
File Size : 47,8 Mb
Release : 2012-09-10
Category : Psychology
ISBN : 9781135694425

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Statistics As Principled Argument by Robert P. Abelson Pdf

In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.

Statistical Inference as Severe Testing

Deborah G. Mayo
Statistical Inference as Severe Testing Book PDF

Author : Deborah G. Mayo
Publisher : Cambridge University Press
Page : 503 pages
File Size : 41,7 Mb
Release : 2018-09-20
Category : Mathematics
ISBN : 9781107054134

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Statistical Inference as Severe Testing by Deborah G. Mayo Pdf

Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.

Serious Stat

Thomas Baguley
Serious Stat Book PDF

Author : Thomas Baguley
Publisher : Bloomsbury Publishing
Page : 864 pages
File Size : 40,6 Mb
Release : 2018-01-24
Category : Psychology
ISBN : 9780230363557

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Serious Stat by Thomas Baguley Pdf

Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.

Bayesian Data Analysis, Third Edition

Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Bayesian Data Analysis Third Edition Book PDF

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 42,9 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

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Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Common Errors in Statistics (and How to Avoid Them)

Phillip I. Good,James W. Hardin
Common Errors in Statistics and How to Avoid Them Book PDF

Author : Phillip I. Good,James W. Hardin
Publisher : John Wiley & Sons
Page : 231 pages
File Size : 48,8 Mb
Release : 2011-09-20
Category : Mathematics
ISBN : 9781118211274

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Common Errors in Statistics (and How to Avoid Them) by Phillip I. Good,James W. Hardin Pdf

Praise for the Second Edition "All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice." —Journal of Applied Statistics ". . . a very engaging and valuable book for all who use statistics in any setting." —CHOICE ". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well." —MAA Reviews Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research. The Third Edition has been considerably expanded and revised to include: A new chapter on data quality assessment A new chapter on correlated data An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs Revamped exercises with a stronger emphasis on solutions An extended chapter on report preparation New sections on factor analysis as well as Poisson and negative binomial regression Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.

Modern Statistics with R

Måns Thulin
Modern Statistics with R Book PDF

Author : Måns Thulin
Publisher : BoD - Books on Demand
Page : 598 pages
File Size : 46,8 Mb
Release : 2021-07-28
Category : Mathematics
ISBN : 9789152701515

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Modern Statistics with R by Måns Thulin Pdf

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and computing confidence intervals. - Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. - Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. - Ethics in statistics - ethical issues and good statistical practice. - R programming - writing code that is fast, readable, and free from bugs. Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions. Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.

Statistics for Making Decisions

Nicholas T. Longford
Statistics for Making Decisions Book PDF

Author : Nicholas T. Longford
Publisher : Chapman & Hall/CRC
Page : 0 pages
File Size : 50,9 Mb
Release : 2022-09-26
Category : Decision making
ISBN : 0367342707

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Statistics for Making Decisions by Nicholas T. Longford Pdf

Making decisions is a ubiquitous mental activity in our private and professional or public lives. It entails choosing one course of action from an available shortlist of options. Statistics for Making Decisions places decision making at the centre of statistical inference, proposing its theory as a new paradigm for statistical practice. The analysis in this paradigm is earnest about prior information and the consequences of the various kinds of errors that may be committed. Its conclusion is a course of action tailored to the perspective of the specific client or sponsor of the analysis. The author's intention is a wholesale replacement of hypothesis testing, indicting it with the argument that it has no means of incorporating the consequences of errors which self-evidently matter to the client. The volume appeals to the analyst who deals with the simplest statistical problems of comparing two samples (which one has a greater mean or variance), or deciding whether a parameter is positive or negative. It combines highlighting the deficiencies of hypothesis testing with promoting a principled solution based on the idea of a currency for error, of which we want to spend as little as possible. This is implemented by selecting the option for which the expected loss is smallest (the Bayes rule). The price to pay is the need for a more detailed description of the options, and eliciting and quantifying the consequences (ramifications) of the errors. This is what our clients do informally and often inexpertly after receiving outputs of the analysis in an established format, such as the verdict of a hypothesis test or an estimate and its standard error. As a scientific discipline and profession, statistics has a potential to do this much better and deliver to the client a more complete and more relevant product. Nicholas T. Longford is a senior statistician at Imperial College, London, specialising in statistical methods for neonatal medicine. His interests include causal analysis of observational studies, decision theory, and the contest of modelling and design in data analysis. His longer-term appointments in the past include Educational Testing Service, Princeton, NJ, USA, de Montfort University, Leicester, England, and directorship of SNTL, a statistics research and consulting company. He is the author of over 100 journal articles and six other monographs on a variety of topics in applied statistics.

Statistics

Frederick L. Coolidge
Statistics Book PDF

Author : Frederick L. Coolidge
Publisher : SAGE Publications
Page : 571 pages
File Size : 40,6 Mb
Release : 2020-01-10
Category : Psychology
ISBN : 9781506368412

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Statistics by Frederick L. Coolidge Pdf

The Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn’t need to be difficult or dull. This text minimizes students’ anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself." Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint® slides.

Statistical Rethinking

Richard McElreath
Statistical Rethinking Book PDF

Author : Richard McElreath
Publisher : CRC Press
Page : 489 pages
File Size : 41,6 Mb
Release : 2018-01-03
Category : Mathematics
ISBN : 9781482253481

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Statistical Rethinking by Richard McElreath Pdf

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Statistics for Linguists: An Introduction Using R

Bodo Winter
Statistics for Linguists An Introduction Using R Book PDF

Author : Bodo Winter
Publisher : Routledge
Page : 310 pages
File Size : 48,8 Mb
Release : 2019-10-30
Category : Education
ISBN : 9781351677431

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Statistics for Linguists: An Introduction Using R by Bodo Winter Pdf

Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science.

Getting to Yes

Roger Fisher,William Ury,Bruce Patton
Getting to Yes Book PDF

Author : Roger Fisher,William Ury,Bruce Patton
Publisher : Houghton Mifflin Harcourt
Page : 242 pages
File Size : 49,5 Mb
Release : 1991
Category : Business & Economics
ISBN : 0395631246

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Getting to Yes by Roger Fisher,William Ury,Bruce Patton Pdf

Describes a method of negotiation that isolates problems, focuses on interests, creates new options, and uses objective criteria to help two parties reach an agreement.

Statistical Models

A. C. Davison
Statistical Models Book PDF

Author : A. C. Davison
Publisher : Cambridge University Press
Page : 0 pages
File Size : 48,5 Mb
Release : 2008-06-30
Category : Mathematics
ISBN : 0521734495

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Statistical Models by A. C. Davison Pdf

Models and likelihood are the backbone of modern statistics and data analysis. The coverage is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics. Anthony Davison blends theory and practice to provide an integrated text for advanced undergraduate and graduate students, researchers and practicioners. Its comprehensive coverage makes this the standard text and reference in the subject.