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A First Course In Linear Regression

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A First Course In Linear Model Theory

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Author : Nalini Ravishanker
language : en
Publisher: CRC Press
Release Date : 2021-10-18

A First Course In Linear Model Theory written by Nalini Ravishanker and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-18 with Mathematics categories.

Thoroughly updated throughout, A First Course in Linear Model Theory, Second Edition is an intermediate-level statistics text that fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the authors introduce to students the mathematical and statistical concepts and tools that form a foundation for studying the theory and applications of both univariate and multivariate linear models. In addition to adding R functionality, this second edition features three new chapters and several sections on new topics that are extremely relevant to the current research in statistical methodology. Revised or expanded topics include linear fixed, random and mixed effects models, generalized linear models, Bayesian and hierarchical linear models, model selection, multiple comparisons, and regularized and robust regression. New to the Second Edition: Coverage of inference for linear models has been expanded into two chapters. Expanded coverage of multiple comparisons, random and mixed effects models, model selection, and missing data. A new chapter on generalized linear models (Chapter 12). A new section on multivariate linear models in Chapter 13, and expanded coverage of the Bayesian linear models and longitudinal models. A new section on regularized regression in Chapter 14. Detailed data illustrations using R. The authors' fresh approach, methodical presentation, wealth of examples, use of R, and introduction to topics beyond the classical theory set this book apart from other texts on linear models. It forms a refreshing and invaluable first step in students' study of advanced linear models, generalized linear models, nonlinear models, and dynamic models.

A First Course In Linear Regression

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Author : Mary Sue Younger
language : en
Publisher: Brooks/Cole
Release Date : 1985

A First Course In Linear Regression written by Mary Sue Younger and has been published by Brooks/Cole this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.

A First Course In Linear Regression

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Author : Mary Sue Younger
language : en
Publisher: Brooks/Cole
Release Date : 1985

A First Course In Linear Regression

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Author : M. S. Younger
language : en
Publisher:
Release Date : 1979

A First Course In Linear Regression written by M. S. Younger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with categories.

A First Course In Linear Model Theory

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Author : Nalini Ravishanker
language : en
Publisher: CRC Press
Release Date : 2020-09-14

This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the author's introduces students to the mathematical and statistical concepts and tools that form a foundation

A First Course In Systems Biology

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Author : Eberhard Voit
language : en
Publisher: Taylor & Francis
Release Date : 2025-01-20

A First Course In Systems Biology written by Eberhard Voit and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-20 with Science categories.

A First Course in Systems Biology, Third Edition is an introduction to the growing field of systems biology for advanced undergraduates and graduate students. Its focus is the design and analysis of computational models and their applications to diverse biomedical phenomena, from simple networks and kinetics to complex pathway systems, signal transduction, personalized medicine, and interacting populations. The book begins with the fundamentals of computational modeling, then reviews features of the molecular inventories that bring biological systems to life and ends with case studies that reflect some of the frontiers in systems biology. In this way, the First Course provides the reader with a comprehensive background and with access to methods for executing standard tasks of biomedical systems analysis, exposure to the modern literature, and a foundation for launching into specialized projects that address biomedical questions with theoretical and computational means. This third edition has been thoroughly updated. It provides an introduction to agent-based and multiscale modeling, a deeper account of biological design principles, and the optimization of metabolic flux distributions. This edition also discusses novel topics of synthetic biology, personalized medicine, and virtual clinical trials that are just emerging on the horizon of this field.

Regression

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Author : N. H. Bingham
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-17

Regression written by N. H. Bingham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-17 with Mathematics categories.

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.

A First Course In Causal Inference

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Author : Peng Ding
language : en
Publisher: CRC Press
Release Date : 2024-07-31

A First Course In Causal Inference written by Peng Ding and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Mathematics categories.

The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught over the past seven years, only requires basic knowledge of probability theory, statistical inference, and linear and logistic regressions. It assumes minimal knowledge of causal inference, and reviews basic probability and statistics in the appendix. It covers causal inference from a statistical perspective and includes examples and applications from biostatistics and econometrics. Key Features: All R code and data sets available at Harvard Dataverse. Solutions manual available for instructors. Includes over 100 exercises. This book is suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments.

Exercises And Solutions In Biostatistical Theory

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Author : Lawrence Kupper
language : en
Publisher: CRC Press
Release Date : 2010-11-09

Exercises And Solutions In Biostatistical Theory written by Lawrence Kupper and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-09 with Mathematics categories.

Drawn from nearly four decades of Lawrence L. Kupper’s teaching experiences as a distinguished professor in the Department of Biostatistics at the University of North Carolina, Exercises and Solutions in Biostatistical Theory presents theoretical statistical concepts, numerous exercises, and detailed solutions that span topics from basic probability to statistical inference. The text links theoretical biostatistical principles to real-world situations, including some of the authors’ own biostatistical work that has addressed complicated design and analysis issues in the health sciences. This classroom-tested material is arranged sequentially starting with a chapter on basic probability theory, followed by chapters on univariate distribution theory and multivariate distribution theory. The last two chapters on statistical inference cover estimation theory and hypothesis testing theory. Each chapter begins with an in-depth introduction that summarizes the biostatistical principles needed to help solve the exercises. Exercises range in level of difficulty from fairly basic to more challenging (identified with asterisks). By working through the exercises and detailed solutions in this book, students will develop a deep understanding of the principles of biostatistical theory. The text shows how the biostatistical theory is effectively used to address important biostatistical issues in a variety of real-world settings. Mastering the theoretical biostatistical principles described in the book will prepare students for successful study of higher-level statistical theory and will help them become better biostatisticians.

Applied Stochastic Modelling

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Author : Byron J.T. Morgan
language : en
Publisher: CRC Press
Release Date : 2008-12-02

Applied Stochastic Modelling written by Byron J.T. Morgan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-02 with Mathematics categories.

Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and

A First Course In Linear Regression

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