Understanding Regression Analysis: An Introductory Guide, Schroeder Larry D., Sjoquist David L., Stephan Pau
Старое издание
Автор: Michael Patrick Allen Название: Understanding Regression Analysis ISBN: 0306456486 ISBN-13(EAN): 9780306456480 Издательство: Springer Рейтинг: Цена: 125770.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics.
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience.
Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.
By the time you reach the end of the book (and online material) you will have gained:
A clear appreciation of the importance of a statistical approach to the design of your experiments,
A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.
The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.
Автор: Darlington Richard B., Hayes Andrew F. Название: Regression Analysis and Linear Models: Concepts, Applications, and Implementation ISBN: 1462521134 ISBN-13(EAN): 9781462521135 Издательство: Taylor&Francis Рейтинг: Цена: 83690.00 T Наличие на складе: Невозможна поставка. Описание: Ephasizing 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.
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more.
The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important.
Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding
Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more
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