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## Métodos Estatísticos Para as Ciências Sociais livro de referência

- Autor: Alan Agresti
- Editora: Penso
- Data de publicação: 2012-02-09
- ISBN: 8563899570
- Páginas: 664 pages
- Tag: metodos, estatisticos, ciencias, sociais

Escrita de forma clara e didática, a obra aborda temas estatísticos importantes como estatística descritiva; distribuições de probabilidade; amostragem e estimação; análise de variáveis categóricas e análise de variância. Os autores passam por diferentes níveis de complexidade, por isso é ideal para alunos de graduação e de pós-graduação.

## Métodos Estatísticos para as Ciências Sociais livro de referência

- Autor: Alan Agresti
- Editora: Penso
- Data de publicação: 2017-08-03
- Tag: metodos, estatisticos, ciencias, sociais

Escrita de forma clara e didática, a obra aborda temas estatísticos importantes como estatística descritiva; distribuições de probabilidade; amostragem e estimação; análise de variáveis categóricas e análise de variância. Os autores passam por diferentes níveis de complexidade, por isso é ideal para alunos de graduação e de pós-graduação.

## Statistical Methods for the Social Sciences: Pearson New International Edition livro de referência

- Autor: Alan Agresti
- Editora: Pearson
- Data de publicação: 2013-08-27
- Páginas: 568 pages
- Tag: statistical, methods, social, sciences, pearson, international, edition

The book presents an introduction to statistical methods for students majoring in social science disciplines. No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).

The book contains sufficient material for a two-semester sequence of courses. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course.

Datasets and other resources (where applicable) for this book are available here.

## Statistical Methods for the Social Sciences, Global Edition livro de referência

- Autor: Alan Agresti
- Editora: Pearson
- Data de publicação: 2018-02-13
- Páginas: 568 pages
- Tag: statistical, methods, social, sciences, global, edition

*For courses in Statistical Methods for the Social Sciences.*

**Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts**introduces statistical methods to students majoring in social science disciplines. With an emphasis on concepts and applications, this book assumes no previous knowledge of statistics and only a minimal mathematical background. It contains sufficient material for a two-semester course. The

*Statistical Methods for the Social Sciences***5th Edition**uses examples and exercises with a variety of “real data.” It includes more illustrations of statistical software for computations and takes advantage of the outstanding applets to explain key concepts, such as sampling distributions and conducting basic data analyses. It continues to downplay mathematics—often a stumbling block for students—while avoiding reliance on an overly simplistic recipe-based approach to statistics.

## Statistics: The Art and Science of Learning from Data, Global Edition livro de referência

- Autor: Alan Agresti
- Editora: Pearson
- Data de publicação: 2017-01-18
- Tag: statistics, science, learning, global, edition

*For courses in introductory statistics.*

**The Art and Science of Learning from Data**

* *

** Statistics: The Art and Science of Learning from Data, Fourth Edition,** takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises.

The authors believe that it’s important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data.

**MyStatLab™ not included. **Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

**MyStatLab** is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

## An Introduction to Categorical Data Analysis livro de referência

- Autor: Alan Agresti
- Editora: John Wiley & Sons
- Data de publicação: 2007-04-17
- ISBN: 0471226181
- Páginas: 400 pages
- Tag: introduction, categorical, analysis

**Praise for the First Edition**

"This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended."

*Short Book Reviews*

"Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few."

*Journal of Quality Technology*

"Alan Agresti has written another brilliant account of the analysis of categorical data."

The Statistician

The use of statistical methods for categorical data is ever increasing in today′s world. *An Introduction to Categorical Data Analysis, Second Edition* provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi–squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses.

This Second Edition features:

- Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models
- A unified perspective based on generalized linear models
- An emphasis on logistic regression modeling
- An appendix that demonstrates the use of SAS(r) for all methods
- An entertaining historical perspective on the development of the methods
- Specialized methods for ordinal data, small samples, multicategory data, and matched pairs
- More than 100 analyses of real data sets and nearly 300 exercises

Written in an applied, nontechnical style, the book illustrates methods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more.

*An Introduction to Categorical Data Analysis, Second Edition* is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control.

## Foundations of Linear and Generalized Linear Models (Wiley Series in Probability and Statistics) livro de referência

- Autor: Alan Agresti
- Editora: Wiley
- Data de publicação: 2015-01-15
- Páginas: 480 pages
- Tag: foundations, linear, generalized, linear, models, wiley, series, probability, statistics

**A valuable overview of the most important ideas and results in statistical modeling**

Written by a highly-experienced author, *Foundations of Linear and Generalized Linear Models *is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding.

The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, *Foundations of**Linear and Generalized Linear Models *also features:

- An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods
- An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems
- Numerous examples that use R software for all text data analyses
- More than 400 exercises for readers to practice and extend the theory, methods, and data analysis
- A supplementary website with datasets for the examples and exercises

*Foundations of Linear and Generalized Linear Models*is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.

## Categorical Data Analysis (Wiley Series in Probability and Statistics) livro de referência

- Autor: Alan Agresti
- Editora: Wiley
- Data de publicação: 2013-04-08
- Páginas: 744 pages
- Tag: categorical, analysis, wiley, series, probability, statistics

**Praise for the Second Edition**

"A must-have book for anyone expecting to do research and/or applications in categorical data analysis."

—*Statistics in Medicine*

"It is a total delight reading this book."

—*Pharmaceutical Research*

"If you do any analysis of categorical data, this is an essential desktop reference."

—*Technometrics*

The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, this book offers a comprehensive treatment of the most important methods for categorical data analysis.

*Categorical Data Analysis, Third Edition* summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial loglinear models for discrete data with normal regression for continuous data. This edition also features:

- An emphasis on logistic and probit regression methods for binary, ordinal, and nominal responses for independent observations and for clustered data with marginal models and random effects models
- Two new chapters on alternative methods for binary response data, including smoothing and regularization methods, classification methods such as linear discriminant analysis and classification trees, and cluster analysis
- New sections introducing the Bayesian approach for methods in that chapter
- More than 100 analyses of data sets and over 600 exercises
- Notes at the end of each chapter that provide references to recent research and topics not covered in the text, linked to a bibliography of more than 1,200 sources
- A supplementary website showing how to use R and SAS; for all examples in the text, with information also about SPSS and Stata and with exercise solutions

*Categorical Data Analysis, Third Edition* is an invaluable tool for statisticians and methodologists, such as biostatisticians and researchers in the social and behavioral sciences, medicine and public health, marketing, education, finance, biological and agricultural sciences, and industrial quality control.

## Analysis of Ordinal Categorical Data (Wiley Series in Probability and Statistics) livro de referência

- Autor: Alan Agresti
- Editora: Wiley
- Data de publicação: 2012-06-19
- Páginas: 424 pages
- Tag: analysis, ordinal, categorical, wiley, series, probability, statistics

Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy.

*Analysis of Ordinal Categorical Data, Second Edition*provides an introduction to basic descriptive and inferential methods for categorical data, giving thorough coverage of new developments and recent methods. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. Practitioners of statistics in government, industry (particularly pharmaceutical), and academia will want this new edition.## An Introduction to Categorical Data Analysis livro de referência

- Autor: Alan Agresti
- Editora: Wiley-Interscience
- Data de publicação: 2007-03-23
- Páginas: 400 pages
- Tag: introduction, categorical, analysis

**Praise for the First Edition**

"This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended."

—*Short Book Reviews*

"Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few."

—*Journal of Quality Technology*

"Alan Agresti has written another brilliant account of the analysis of categorical data."

—The Statistician

The use of statistical methods for categorical data is ever increasing in today's world. *An Introduction to Categorical Data Analysis, Second Edition* provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses.

This Second Edition features:

- Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models
- A unified perspective based on generalized linear models
- An emphasis on logistic regression modeling
- An appendix that demonstrates the use of SAS(r) for all methods
- An entertaining historical perspective on the development of the methods
- Specialized methods for ordinal data, small samples, multicategory data, and matched pairs
- More than 100 analyses of real data sets and nearly 300 exercises

Written in an applied, nontechnical style, the book illustrates methods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more.

*An Introduction to Categorical Data Analysis, Second Edition* is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control.