Regression

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Handbook of Regression Modeling in People Analytics

Author : Keith McNulty
Publisher : CRC Press
ISBN 13 : 1000427897
Total Pages : 272 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Handbook of Regression Modeling in People Analytics by : Keith McNulty

Download or read book Handbook of Regression Modeling in People Analytics written by Keith McNulty and published by CRC Press. This book was released on 2021-07-29 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features: 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) Clear step-by-step instructions on executing the analyses Clear guidance on how to interpret results Primary instruction in R but added sections for Python coders Discussion exercises and data exercises for each of the main chapters Final chapter of practice material and datasets ideal for class homework or project work.

Regression and Other Stories

Author : Andrew Gelman
Publisher : Cambridge University Press
ISBN 13 : 110702398X
Total Pages : 551 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Regression and Other Stories by : Andrew Gelman

Download or read book Regression and Other Stories written by Andrew Gelman and published by Cambridge University Press. This book was released on 2020-07-23 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.

Regression Modeling Strategies

Author : Frank E. Harrell
Publisher : Springer Science & Business Media
ISBN 13 : 147573462X
Total Pages : 583 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Regression Modeling Strategies by : Frank E. Harrell

Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".

Learning Statistics with R

Author : Daniel Navarro
Publisher : Lulu.com
ISBN 13 : 1326189727
Total Pages : 617 pages
Book Rating : 4.3/5 (261 download)

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Book Synopsis Learning Statistics with R by : Daniel Navarro

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Linear Regression

Author : David J. Olive
Publisher : Springer
ISBN 13 : 331955252X
Total Pages : 499 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Linear Regression by : David J. Olive

Download or read book Linear Regression written by David J. Olive and published by Springer. This book was released on 2017-04-18 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response transformations for multiple linear regression or experimental design models. This text is for graduates and undergraduates with a strong mathematical background. The prerequisites for this text are linear algebra and a calculus based course in statistics.

Data Analysis Using Regression and Multilevel/Hierarchical Models

Author : Andrew Gelman
Publisher : Cambridge University Press
ISBN 13 : 9780521686891
Total Pages : 654 pages
Book Rating : 4.6/5 (868 download)

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Book Synopsis Data Analysis Using Regression and Multilevel/Hierarchical Models by : Andrew Gelman

Download or read book Data Analysis Using Regression and Multilevel/Hierarchical Models written by Andrew Gelman and published by Cambridge University Press. This book was released on 2007 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Applied Regression Modeling

Author : Iain Pardoe
Publisher : John Wiley & Sons
ISBN 13 : 1118345045
Total Pages : 319 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Applied Regression Modeling by : Iain Pardoe

Download or read book Applied Regression Modeling written by Iain Pardoe and published by John Wiley & Sons. This book was released on 2013-01-07 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.

Regression & Linear Modeling

Author : Jason W. Osborne
Publisher : SAGE Publications
ISBN 13 : 1506302750
Total Pages : 489 pages
Book Rating : 4.5/5 (63 download)

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Book Synopsis Regression & Linear Modeling by : Jason W. Osborne

Download or read book Regression & Linear Modeling written by Jason W. Osborne and published by SAGE Publications. This book was released on 2016-03-24 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

Regression

Author : N. H. Bingham
Publisher : Springer Science & Business Media
ISBN 13 : 1848829698
Total Pages : 293 pages
Book Rating : 4.8/5 (488 download)

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Book Synopsis Regression by : N. H. Bingham

Download or read book Regression written by N. H. Bingham and published by Springer Science & Business Media. This book was released on 2010-09-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential. Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions. The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments. Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh’s Probability Models, and T. S. Blyth & E.F. Robertsons’ Basic Linear Algebra and Further Linear Algebra.

Regression Methods in Biostatistics

Author : Eric Vittinghoff
Publisher : Springer Science & Business Media
ISBN 13 : 1461413524
Total Pages : 526 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Regression Methods in Biostatistics by : Eric Vittinghoff

Download or read book Regression Methods in Biostatistics written by Eric Vittinghoff and published by Springer Science & Business Media. This book was released on 2012 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.

The SAGE Handbook of Regression Analysis and Causal Inference

Author : Henning Best
Publisher : SAGE
ISBN 13 : 1473908353
Total Pages : 425 pages
Book Rating : 4.4/5 (739 download)

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Book Synopsis The SAGE Handbook of Regression Analysis and Causal Inference by : Henning Best

Download or read book The SAGE Handbook of Regression Analysis and Causal Inference written by Henning Best and published by SAGE. This book was released on 2013-12-20 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.

Applied Logistic Regression

Author : David W. Hosmer, Jr.
Publisher : John Wiley & Sons
ISBN 13 : 0471654027
Total Pages : 397 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis Applied Logistic Regression by : David W. Hosmer, Jr.

Download or read book Applied Logistic Regression written by David W. Hosmer, Jr. and published by John Wiley & Sons. This book was released on 2004-10-28 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

A Modern Approach to Regression with R

Author : Simon Sheather
Publisher : Springer Science & Business Media
ISBN 13 : 0387096086
Total Pages : 398 pages
Book Rating : 4.3/5 (87 download)

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Book Synopsis A Modern Approach to Regression with R by : Simon Sheather

Download or read book A Modern Approach to Regression with R written by Simon Sheather and published by Springer Science & Business Media. This book was released on 2009-02-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models. Plots are shown to be an important tool for both building regression models and assessing their validity. We shall see that deciding what to plot and how each plot should be interpreted will be a major challenge. In order to overcome this challenge we shall need to understand the mathematical properties of the fitted regression models and associated diagnostic procedures. As such this will be an area of focus throughout the book. In particular, we shall carefully study the properties of resi- als in order to understand when patterns in residual plots provide direct information about model misspecification and when they do not. The regression output and plots that appear throughout the book have been gen- ated using R. The output from R that appears in this book has been edited in minor ways. On the book web site you will find the R code used in each example in the text.

Essential Statistics, Regression, and Econometrics

Author : Gary Smith
Publisher : Academic Press
ISBN 13 : 0128034920
Total Pages : 397 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Essential Statistics, Regression, and Econometrics by : Gary Smith

Download or read book Essential Statistics, Regression, and Econometrics written by Gary Smith and published by Academic Press. This book was released on 2015-06-08 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Statistics, Regression, and Econometrics, Second Edition, is innovative in its focus on preparing students for regression/econometrics, and in its extended emphasis on statistical reasoning, real data, pitfalls in data analysis, and modeling issues. This book is uncommonly approachable and easy to use, with extensive word problems that emphasize intuition and understanding. Too many students mistakenly believe that statistics courses are too abstract, mathematical, and tedious to be useful or interesting. To demonstrate the power, elegance, and even beauty of statistical reasoning, this book provides hundreds of new and updated interesting and relevant examples, and discusses not only the uses but also the abuses of statistics. The examples are drawn from many areas to show that statistical reasoning is not an irrelevant abstraction, but an important part of everyday life. - Includes hundreds of updated and new, real-world examples to engage students in the meaning and impact of statistics - Focuses on essential information to enable students to develop their own statistical reasoning - Ideal for one-quarter or one-semester courses taught in economics, business, finance, politics, sociology, and psychology departments, as well as in law and medical schools - Accompanied by an ancillary website with an instructors solutions manual, student solutions manual and supplementing chapters

Regression Analysis and Linear Models

Author : Richard B. Darlington
Publisher : Guilford Publications
ISBN 13 : 1462527981
Total Pages : 689 pages
Book Rating : 4.4/5 (625 download)

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Book Synopsis Regression Analysis and Linear Models by : Richard B. Darlington

Download or read book Regression Analysis and Linear Models written by Richard B. Darlington and published by Guilford Publications. This book was released on 2016-08-22 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book's examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable’s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.

Multiple Regression and Beyond

Author : Timothy Z. Keith
Publisher : Routledge
ISBN 13 : 1351667939
Total Pages : 640 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Multiple Regression and Beyond by : Timothy Z. Keith

Download or read book Multiple Regression and Beyond written by Timothy Z. Keith and published by Routledge. This book was released on 2019-01-14 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This book: • Covers both MR and SEM, while explaining their relevance to one another • Includes path analysis, confirmatory factor analysis, and latent growth modeling • Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises • Extensive use of figures and tables providing examples and illustrating key concepts and techniques New to this edition: • New chapter on mediation, moderation, and common cause • New chapter on the analysis of interactions with latent variables and multilevel SEM • Expanded coverage of advanced SEM techniques in chapters 18 through 22 • International case studies and examples • Updated instructor and student online resources

Semiparametric Regression

Author : David Ruppert
Publisher : Cambridge University Press
ISBN 13 : 9780521785167
Total Pages : 408 pages
Book Rating : 4.7/5 (851 download)

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Book Synopsis Semiparametric Regression by : David Ruppert

Download or read book Semiparametric Regression written by David Ruppert and published by Cambridge University Press. This book was released on 2003-07-14 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Even experts on semiparametric regression should find something new here.