Handbook of regression modeling in people analytics, Mcnulty, Keith
Автор: Mcnulty, Keith Название: Handbook of regression modeling in people analytics ISBN: 1032041749 ISBN-13(EAN): 9781032041742 Издательство: Taylor&Francis Рейтинг: Цена: 10258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Paulson, Daryl S. Название: Handbook of Regression and Modeling ISBN: 1032477857 ISBN-13(EAN): 9781032477855 Издательство: Taylor&Francis Рейтинг: Цена: 7042.00 р. Наличие на складе: Нет в наличии.
Автор: Paulson, Daryl S. Название: Handbook of Regression and Modeling ISBN: 157444610X ISBN-13(EAN): 9781574446104 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Нет в наличии.
Автор: Mcnulty, Keith Название: Handbook of graphs and networks in people analytics ISBN: 1032204974 ISBN-13(EAN): 9781032204970 Издательство: Taylor&Francis Рейтинг: Цена: 10258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form.
Автор: Mcnulty, Keith Название: Handbook of graphs and networks in people analytics ISBN: 1032211245 ISBN-13(EAN): 9781032211244 Издательство: Taylor&Francis Рейтинг: Цена: 27562.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form.
Автор: McGibney Название: Applied Linear Regression for Business Analytics with R ISBN: 303121479X ISBN-13(EAN): 9783031214790 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.
Автор: Mcgibney, Daniel P. Название: Applied linear regression for business analytics with r ISBN: 303121482X ISBN-13(EAN): 9783031214820 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Chatterjee Samprit, Simonoff Jeffrey S. Название: Handbook of Regression Analysis with Applications in R ISBN: 1119392373 ISBN-13(EAN): 9781119392378 Издательство: Wiley Рейтинг: Цена: 17574.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Handbook and reference guide for students and practitioners of statistical regression-based analyses in R
Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data.
The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include:
In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website.
Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.
Автор: Bradley A. Hartlaub Название: STAT2: Modeling with Regression and ANOVA ISBN: 1319054072 ISBN-13(EAN): 9781319054076 Издательство: Macmillan Learning Рейтинг: Цена: 15244.00 р. Наличие на складе: Нет в наличии.
Описание: The book will appeal to a diverse audience, including advocates and sceptics, academics and practitioners, transitional justice specialists and readers from other sectors (development, peace-building and human rights), and to a genuinely multi-disciplinary cohort of scholars. Its value lies in its contribution to both conceptual and practice-based thinking on transformative justice.
Автор: Knafl George J., Ding Kai Название: Adaptive Regression for Modeling Nonlinear Relationships ISBN: 3319816381 ISBN-13(EAN): 9783319816388 Издательство: Springer Рейтинг: Цена: 11225.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes.
Описание: It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data.
Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.
New to the Second Edition
Reorganized to focus on unbalanced data
Reworked balanced analyses using methods for unbalanced data
Introductions to nonparametric and lasso regression
Introductions to general additive and generalized additive models
Examination of homologous factors
Unbalanced split plot analyses
Extensions to generalized linear models
R, Minitab(R), and SAS code on the author's website
The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.
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