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Statistical Foundations Reasoning And Inference For Science And Data Science at Meripustak

Statistical Foundations Reasoning And Inference For Science And Data Science by Goeran Kauermann, Helmut Küchenhoff, Springer

Books from same Author: Goeran Kauermann, Helmut Küchenhoff

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  • General Information  
    Author(s)Goeran Kauermann, Helmut Küchenhoff
    PublisherSpringer
    ISBN9783030698263
    Pages356
    BindingHardbound
    LanguageEnglish
    Publish YearNovember 2021

    Description

    Springer Statistical Foundations Reasoning And Inference For Science And Data Science by Goeran Kauermann, Helmut Küchenhoff

    This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master's students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills. Introduction.- Background in Probability.- Parametric Statistical Models.- Maximum Likelihood Inference.- Bayesian Statistics.- Statistical Decisions.- Regression.- Bootstrapping.- Model Selection and Model Averaging.- Multivariate and Extreme Value Distributions.- Missing and Deficient Data.- Experiments and Causality.