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  • Multiple Comparisons Using R

    Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-pro ... Leer más

    $140.99 USD

  • A Handbook of Statistical Analyses using R

    Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.New to the Third Edition ... Leer más

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  • Causal Inference in Statistics

    A Primer

    CAUSAL INFERENCE IN STATISTICSA PrimerCausality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written ... Leer más

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  • Artificial Intelligence

    With an Introduction to Machine Learning, Second Edition

    Series series Chapman & Hall/CRC Artificial Intelligence and Robotics Series
    The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.The book is divided into five ... Leer más

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  • Elements of Causal Inference

    Foundations and Learning Algorithms

    Series series Adaptive Computation and Machine Learning series
    A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data.After explaining the ... Leer más

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  • Sample Size Calculations in Clinical Research

    Series series Chapman & Hall/CRC Biostatistics Series
    Praise for the Second Edition:"… this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics"This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, ... Leer más

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  • Network Psychometrics with R

    A Guide for Behavioral and Social Scientists

    A systematic, innovative introduction to the field of network analysis, Network Psychometrics with R: A Guide for Behavioral and Social Scientists provides a comprehensive overview of and guide to both the theoretical foundations of network psychometrics as well as modelling techniques developed from this perspective.Written by pioneers in the field, this textbook showcases cutting-edge methods in ... Leer más

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  • Essential Statistical Methods for Medical Statistics

    Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development ... Leer más

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  • Experimental Design

    Procedures for the Behavioral Sciences

    de Roger E. Kirk ...
    This classic text, with a reputuation for accessibility and readability, has been revised and updated to make learning design concepts even easier. Roger E. Kirk shows how three simple experimental designs can be combined to form a variety of complex designs. He provides diagrams illustrating how subjects are assigned to treatments and treatment combinations. New terms are emphasized in boldface ... Leer más

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  • Statistical Learning for Biomedical Data

    Series series Practical Guides to Biostatistics and Epidemiology
    This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines ... Leer más

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  • Machine Learning from Weak Supervision

    An Empirical Risk Minimization Approach

    Series series Adaptive Computation and Machine Learning series
    Fundamental theory and practical algorithms of weakly supervised classification, emphasizing an approach based on empirical risk minimization.Standard machine learning techniques require large amounts of labeled data to work well. When we apply machine learning to problems in the physical world, however, it is extremely difficult to collect such quantities of labeled data. In this book Masashi ... Leer más

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  • Mathematical Statistics

    Explores mathematical statistics in its entirety—from the fundamentals to modern methodsThis book introduces readers to point estimation, confidence intervals, and statistical tests. Based on the general theory of linear models, it provides an in-depth overview of the following: analysis of variance (ANOVA) for models with fixed, random, and mixed effects; regression analysis is also first ... Leer más

    $77.00 USD