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Applied Regression Analysis

Autor: John O. Rawlings , Sastry G. Pantula , David A. Dickey

Número de Páginas: 660

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course. Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key ...

Applied Regression Analysis

Autor: Norman Richard Draper

Número de Páginas: 407

Applied Regression Analysis in Econometrics

Autor: Howard E. Doran

Número de Páginas: 400

A textbook for a one-semester course for advanced undergraduate and graduate students in economics. Covers regression techniques in the context of single equation econometric models, featuring MINITAB and SHAZAM software examples for attacking real-world problems. Annotation copyright Book News, Inc

Applied Regression Analysis

Autor: Norman Richard Draper , Harry Smith

Número de Páginas: 428

This book provides a standard, basic course in multiple linear regression, but it also includes material that either has not previously appeared in a textbook or, if it has appeared, is not generally available.

Applied Regression Analysis

Autor: John O. Rawlings , Sastry G. Pantula , David A. Dickey

Número de Páginas: 680

Applied Regression Analysis

Autor: Christer Thrane

Número de Páginas: 192

This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and perform it to perfection. This non-technical point of departure is complemented by practical examples of real-life data analysis using statistics software such as Stata, R and SPSS. Parts 1 and 2 of the book cover the basics, such as simple linear regression, multiple linear regression, how to interpret the output from statistics programs, significance testing and the key regression assumptions. Part 3 deals with how to practically handle violations of the classical linear regression assumptions, regression modeling for categorical y-variables and instrumental variable (IV) regression. Part 4 puts the various purposes of, or motivations for, regression into the wider context of writing a scholarly report and points to some extensions to related statistical techniques. This book is written primarily for those who need to do regression analysis in practice, and not...

Applied Regression Analysis

Autor: Norman Richard Draper , H. Smith

Applied Regression Analysis and Generalized Linear Models

Autor: John Fox

Número de Páginas: 612

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.

Applied Regression Analysis and Other Multivariable Methods

Autor: David G. Kleinbaum , Lawrence L. Kupper

Número de Páginas: 576

Applied Regression

Autor: Colin Lewis-beck , Michael Lewis-beck

Número de Páginas: 71

Known for its readability and clarity, this Second Edition of the best-selling Applied Regression provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. The authors then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.

Applied Regression Analysis

Autor: Norman Richard Draper (and Smith (harry) Ph.d.)

Número de Páginas: 0

Applied Regression

Autor: Michael Lewis-beck

Número de Páginas: 88

Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.

Applied Regression Analysis and Experimental Design

Autor: Brook

Applied Regression

Autor: Colin Lewis-beck , Michael S. Lewis-beck

Known for its readability and clarity, this Second Edition of the best-selling Applied Regression provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. The authors then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.

An R Companion to Applied Regression

Autor: John Fox , Sanford Weisberg

Número de Páginas: 608

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The Third Edition includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this new edition, and include coverage of RStudio and R Markdown.

Applied Regression Analysis

Número de Páginas: 1194

Applied Regression Analysis

Autor: Terry E. Dielman

Número de Páginas: 0

Applied Regression Analysis for Business and Economics

Autor: Terry E. Dielman

Número de Páginas: 600

应用回归分析和其他多元方法

Autor: D.g.·克雷鲍姆

Número de Páginas: 798

本书责任者还有:(美)Lawrence L. Kupper、(美)Keith E. Muller、(美)Azhar Nizam。

An R and S-Plus Companion to Applied Regression

Autor: John Fox

Número de Páginas: 332

"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. " —JEFF GILL, University of Florida, Gainesville

Applied Regression Modeling

Autor: Iain Pardoe

Número de Páginas: 325

"This book offers a practical, concise introduction to regression analysis for upper-level undergraduate students of diverse disciplines including, but not limited to statistics, the social and behavioral sciences, MBA, and vocational studies. The book's overall approach is strongly based on an abundant use of illustrations, examples, case studies, and graphics. It emphasizes major statistical software packages, including SPSS(r), Minitab(r), SAS(r), R, and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided on a specially prepared and maintained author web site. Select software output appears throughout the text. To help readers understand, analyze, and interpret data and make informed decisions in uncertain settings, many of the examples and problems use real-life situations and settings. The book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series and forecasting. New to this edition are more exercises, simplification of tedious topics (such as checking...

Applied Regression Analysis for Business and Economics

Autor: Terry E. Dielman

Applied Regression Analysis, Linear Models, and Related Methods

Autor: John Fox

Número de Páginas: 597

Applied Linear Regression Models

Autor: John Neter , William Wasserman , Michael H. Kutner

Número de Páginas: 694

Applied Linear Regression Models was listed in the newsletter of the Decision Sciences Institute as a classic in its field and a text that should be on every member's shelf. The third edition continues this tradition. It is a successful blend of theory and application. The authors have taken an applied approach, and emphasize understanding concepts; this text demonstrates their approach trough worked-out examples. Sufficient theory is provided so that applications of regression analysis can be carried out with understanding. John Neter is past president of the Decision Science Institute, and Michael Kutner is a top statistician in the health and life sciences area. Applied Linear Regression Models should be sold into the one-term course that focuses on regression models and applications. This is likely to be required for undergraduate and graduate students majoring in allied health, business, economics, and life sciences.

Introduction to Regression Analysis

Autor: Michael A. Golberg , Hokwon A. Cho

Número de Páginas: 453

In order to apply regression analysis effectively, it is necessary to understand both the underlying theory and its practical application. This book explores conventional topics as well as recent practical developments, linking theory with application. Intended to continue from where most basic statistics texts end, it is designed primarily for advanced undergraduates, graduate students and researchers in various fields of engineering, chemical and physical sciences, mathematical sciences and statistics.

Applied Regression Analysis

Autor: Kleinbaum, David G Etc

Número de Páginas: 704

Applying Regression and Correlation

Autor: Jeremy Miles , Mark Shevlin

Número de Páginas: 272

This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach. The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable. Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe are the more complex aspects of regression analysis. The authors gradually extend the model to include aspects of regression analysis such as non-linear regression, logistic regression, and moderator and mediator analysis. These approaches are often presented in terms that are too mathematical for non-statistically inclined students to deal with. Throughout the book maintains a conceptual, non-mathematical focus. Most equations are placed in an appendix, where a detailed...

APPLIED REGRESSION ANALYSIS

Autor: Kleinbaum

Diseño estadístico de experimentos 2a Ed.

Número de Páginas: 300

Applied Regression Analysis for Business Economics

Autor: Dielman

Single Equation Methods in Econometrics

Autor: Howard Edwin Doran , John William Blackstock Guise

Número de Páginas: 336

Regression Diagnostics

Autor: John Fox

Número de Páginas: 100

Explaining the techniques needed for exploring problems that comprise a regression analysis, and for determining whether certain assumptions appear reasonable, this book covers such topics as the problem of collinearity in multiple regression, non-normality of errors, and discrete data.

Applied Regression Modeling

Autor: Iain Pardoe

Número de Páginas: 320

Applied Regression Modeling: A Business Approach represents a consciously fused effort to put all the building blocks of regression modeling in one place (with chapters on statistical foundations and simple linear regression), before constructing a general framework for building multiple linear regression models. The emphasis is on interesting and challenging applications that provide a unified fabric for business settings. An abundant use of graphics is employed throughout the book in an effort to keep the verbiage to an absolute minimum. SPSS, Excel, and R software discussions are incorporated.

Applied Regression Models in the Social Sciences

Autor: Dudley L. Poston, Jr , Eugenia Conde , Layton M. Field

Número de Páginas: 559

An accessible and practical guide to the use of applied regression models in testing and evaluating hypotheses dealing with social relationships, with example applications using relevant statistical methods in both Stata and R.

Regression Analysis

Autor: Jeremy Arkes

Número de Páginas: 423

With the rise of "big data," there is an increasing demand to learn the skills needed to undertake sound quantitative analysis without requiring students to spend too much time on high-level math and proofs. This book provides an efficient alternative approach, with more time devoted to the practical aspects of regression analysis and how to recognize the most common pitfalls. By doing so, the book will better prepare readers for conducting, interpreting, and assessing regression analyses, while simultaneously making the material simpler and more enjoyable to learn. Logical and practical in approach, Regression Analysis teaches: (1) the tools for conducting regressions; (2) the concepts needed to design optimal regression models (based on avoiding the pitfalls); and (3) the proper interpretations of regressions. Furthermore, this book emphasizes honesty in research, with a prevalent lesson being that statistical significance is not the goal of research. This book is an ideal introduction to regression analysis for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better...

Regression Analysis

Autor: Bruce Bowerman , Emily Murphree

Número de Páginas: 220

Regression Analysis: Unified Concepts, Practical Applications, Computer Implementation is a concise and innovative book that gives a complete presentation of applied regression analysis in approximately one-half the space of competing books. With only the modest prerequisite of a basic (non-calculus) statistics course this text is appropriate for the widest possible audience including college juniors, seniors and first-year graduate students in business and statistics, as well as professionals in business and industry. The book is able to accommodate this wide audience because of the unique, integrative approach that is taken to the teaching of regression analysis. Whereas other regression books cover regression in four chapters, beginning with a statistical review, followed by chapters on simple linear regression, matrix algebra and multiple regression, this book introduces regression and covers both simple linear regression and multiple regression in single cohesive chapter. This is made possible through an efficient, integrative discussion of the two techniques. Additionally, in the same chapter (Chapter Two) basic statistical and matrix algebra concepts are introduced as...

Introduction to Linear Regression Analysis

Autor: Douglas C. Montgomery , Elizabeth A. Peck , G. Geoffrey Vining

Número de Páginas: 678

Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics,...

Regression Analysis

Autor: Evan James Williams

Número de Páginas: 232

Applied Regression Models in the Social Sciences

Autor: Dudley L. Poston, Jr , Eugenia Conde , Layton M. Field

Número de Páginas: 560

This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.

Robust Regression

Autor: Lawrence

Número de Páginas: 320

Combining theory, methodology, and applications in a unified survey, this important reference/text presents the most recent results in robust regression analysis, including properties of robust regression techniques, computational issues, forecasting, and robust ridge regression. It provides useful case studies so that students and engineers can apply these techniques to forecasting, quantitative business analysis, econometrics, marketing, statistics, and demand modeling. Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation ... discusses generalized properties of L[subscript p]-estimators ... includes an algorithm for identifying outliers using least absolute value criterion in regression modeling ... reviews redescending M-estimators ... studies L[subscript 1] linear regression ... proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model ... summarizes known properties of L[subscript 1] estimators for time series analysis ... examines ordinary least squares, latent root regression, and a robust regression weighting scheme ... and evaluates results from...