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Introduces readers to the principles of managerial statistics and data science, with an emphasis on statistical literacy of business;
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This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics;
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Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with;
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This is a first-principles-based, practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader;
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This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science;
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unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which;
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maintains, but does not overemphasize mathematical correctness. The book fosters deep understanding of both how to learn from data and how to deal;
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The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics;
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Practical Business Statistics, Seventh Edition, provides a conceptual, realistic, and matter-of-fact approach to managerial statistics;
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Managerial Statistics by Gerald Keller is an established and worldwide bestselling business statistics text. Packed with examples and real;
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in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as;
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This book constitutes the proceedings of the Research School on Statistics and Data Science, RSSDS 2019, held in Melbourne, VIC, Australia;
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Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on;
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Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics;
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can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to;
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Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and;
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Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the;
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international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through;
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without any of the costs involved in data collection. Register-based surveys require their own methodology and the development of these methods;
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principles Introduces Data Wranglin topics such as web scrapping, using regular expressions, and joining and reshaping data tables using the;
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This volume collects the extended versions of papers presented at the SIS Conference Statistics and Data Science: new challenges, new;
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envelopment analysis, and managerial applications. Section A focuses on multiple criteria applications in college course scheduling, offshore;
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For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Introduction to;
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Explore the fundamentals of data analysis, and statistics with case studies using Python. This book will show you how to confidently write;
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of management science methodologies, data envelopment analysis and multi-criteria decision making. The first section is focused on data envelopment;
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Available for the first time in McGraw-Hill's Connect! Principles of Statistics for Engineers and Scientists emphasizes statistical methods;
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This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;
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