Published by Lapis Lucera (edition 2nd ed.), 2017
ISBN 10: 0996916059 ISBN 13: 9780996916059
Language: English
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Paperback. Condition: new. Paperback. "Mastering Applied Statistics in Data Science" offers a comprehensive guide to understanding and applying statistical methods in the field of data science. This book covers essential statistical concepts, techniques, and tools, providing readers with the knowledge and skills needed to analyze data effectively, make informed decisions, and derive actionable insights.Starting with foundational concepts such as descriptive statistics, probability theory, and inferential statistics, this book gradually progresses to more advanced topics such as regression analysis, hypothesis testing, and multivariate analysis. Each concept is explained in a clear and concise manner, with real-world examples and practical applications to illustrate its relevance in data science.Readers will learn how to: Explore and visualize data using descriptive statistics, histograms, and boxplots.Understand probability distributions and their role in statistical modeling.Conduct hypothesis tests to make inferences about population parameters.Build predictive models using regression analysis and machine learning algorithms.Analyze relationships between multiple variables using correlation and regression techniques.Apply advanced statistical methods such as time series analysis, factor analysis, and cluster analysis.Throughout the book, emphasis is placed on hands-on learning, with practical exercises and examples provided to reinforce key concepts. Whether you are a beginner looking to build a solid foundation in applied statistics or an experienced data scientist seeking to deepen your understanding of statistical methods, "Mastering Applied Statistics in Data Science" is an indispensable resource for mastering statistical analysis in the context of data science. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Published by Cham, Springer International Publishing : Imprint: Springer., 2021
ISBN 10: 3030861325 ISBN 13: 9783030861322
Language: English
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First Edition
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Add to basket1st ed. 2021. IX, 159 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Springer Proceedings in Mathematics & Statistics, 375. Sprache: Englisch.
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First Edition
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Add to basketHardcover. Condition: Wie neu. 1. Auflage. privately owned book. as new from the publisher. -This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods. 176 pp. Englisch.
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Add to basketPaperback. Condition: new. Paperback. "Mastering Applied Statistics in Data Science" offers a comprehensive guide to understanding and applying statistical methods in the field of data science. This book covers essential statistical concepts, techniques, and tools, providing readers with the knowledge and skills needed to analyze data effectively, make informed decisions, and derive actionable insights.Starting with foundational concepts such as descriptive statistics, probability theory, and inferential statistics, this book gradually progresses to more advanced topics such as regression analysis, hypothesis testing, and multivariate analysis. Each concept is explained in a clear and concise manner, with real-world examples and practical applications to illustrate its relevance in data science.Readers will learn how to: Explore and visualize data using descriptive statistics, histograms, and boxplots.Understand probability distributions and their role in statistical modeling.Conduct hypothesis tests to make inferences about population parameters.Build predictive models using regression analysis and machine learning algorithms.Analyze relationships between multiple variables using correlation and regression techniques.Apply advanced statistical methods such as time series analysis, factor analysis, and cluster analysis.Throughout the book, emphasis is placed on hands-on learning, with practical exercises and examples provided to reinforce key concepts. Whether you are a beginner looking to build a solid foundation in applied statistics or an experienced data scientist seeking to deepen your understanding of statistical methods, "Mastering Applied Statistics in Data Science" is an indispensable resource for mastering statistical analysis in the context of data science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Add to basketpaperback. Condition: Good. 2nd ed. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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