Asha Gopalakrishnan (19 results)
- Softcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Softcover
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- Softcover
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Paperback. Condition: New. Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields-engineering, science, and the biological, physical, and social sciences-with the statistical tools and techniques essential for data science. This book brid…ges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern machine learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.Designed as a one-semester course, the book provides flexibility for instructors to tailor the content to their curriculum. Whether exploring generalized linear models, mixed-effects models, or dependent data analysis, students will gain a deep understanding of statistical methods and their applications across various domains. By the end of the book, readers will be equipped to make informed decisions, quantify uncertainty, and communicate their findings effectively.This book is not just a learning tool-it's a practical companion for aspiring data scientists seeking to master statistical practice and R programming.
- Softcover
Seller: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
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Paperback. Condition: New. Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields-engineering, science, and the biological, physical, and social sciences-with the statistical tools and techniques essential for data science. This book brid…ges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern machine learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.Designed as a one-semester course, the book provides flexibility for instructors to tailor the content to their curriculum. Whether exploring generalized linear models, mixed-effects models, or dependent data analysis, students will gain a deep understanding of statistical methods and their applications across various domains. By the end of the book, readers will be equipped to make informed decisions, quantify uncertainty, and communicate their findings effectively.This book is not just a learning tool-it's a practical companion for aspiring data scientists seeking to master statistical practice and R programming.
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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US$ 99.10
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Paperback. Condition: Brand New. 288 pages. 9.18x6.12x10.00 inches. In Stock.
- Softcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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US$ 121.97
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Paperback. Condition: Brand New. 288 pages. 9.18x6.12x10.00 inches. In Stock.
Statistical Practice for Data Science
Nalini Ravishanker (University of Connecticut, Storrs, USA)|Asha Gopalakrishnan|Haim Bar
- Softcover
Seller: moluna, Greven, Germanymoluna
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US$ 92.96
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Condition: New. Nalini Ravishanker is Professor in the Department of Statistics at the University of Connecticut (UConn), Storrs. She has a PhD in Statistics and Operations Research from the Stern School of Business, New York University, and a B.Sc. in Statistics.
- Softcover
Seller: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
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Paperback. Condition: New. Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields-engineering, science, and the biological, physical, and social sciences-with the statistical tools and techniques essential for data science. This book brid…ges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern machine learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.Designed as a one-semester course, the book provides flexibility for instructors to tailor the content to their curriculum. Whether exploring generalized linear models, mixed-effects models, or dependent data analysis, students will gain a deep understanding of statistical methods and their applications across various domains. By the end of the book, readers will be equipped to make informed decisions, quantify uncertainty, and communicate their findings effectively.This book is not just a learning tool-it's a practical companion for aspiring data scientists seeking to master statistical practice and R programming.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 84.01
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Taschenbuch. Condition: Neu. Neuware - Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields-engineering, science, and the biological, physical, and social sciences-with the statistical tools and techniques essential for data science. Th…is book bridges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern machine learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.Designed as a one-semester course, the book provides flexibility for instructors to tailor the content to their curriculum. Whether exploring generalized linear models, mixed-effects models, or dependent data analysis, students will gain a deep understanding of statistical methods and their applications across various domains. By the end of the book, readers will be equipped to make informed decisions, quantify uncertainty, and communicate their findings effectively.This book is not just a learning tool-it's a practical companion for aspiring data scientists seeking to master statistical practice and R programming.
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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US$ 93.78
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Paperback. Condition: New. Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields-engineering, science, and the biological, physical, and social sciences-with the statistical tools and techniques essential for data science. This book brid…ges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern machine learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.Designed as a one-semester course, the book provides flexibility for instructors to tailor the content to their curriculum. Whether exploring generalized linear models, mixed-effects models, or dependent data analysis, students will gain a deep understanding of statistical methods and their applications across various domains. By the end of the book, readers will be equipped to make informed decisions, quantify uncertainty, and communicate their findings effectively.This book is not just a learning tool-it's a practical companion for aspiring data scientists seeking to master statistical practice and R programming.
- Hardcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Hardcover
Seller: California Books, Miami, FL, U.S.A.California Books
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US$ 295.00
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- Hardcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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US$ 303.02
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Statistical Practice for Data Science
Nalini Ravishanker (University of Connecticut, Storrs, USA)|Asha Gopalakrishnan|Haim Bar
- Hardcover
Seller: moluna, Greven, Germanymoluna
Contact seller5-star sellerCondition: New
US$ 290.12
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Condition: New. Nalini Ravishanker is Professor in the Department of Statistics at the University of Connecticut (UConn), Storrs. She has a PhD in Statistics and Operations Research from the Stern School of Business, New York University, and a B.Sc. in Statistics.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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US$ 374.26
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Hardcover. Condition: Brand New. 288 pages. 9.18x6.12x10.00 inches. In Stock.
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 402.11
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Buch. Condition: Neu. Neuware - Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields-engineering, science, and the biological, physical, and social sciences-with the statistical tools and techniques essential for data science. This book… bridges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern machine learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.Designed as a one-semester course, the book provides flexibility for instructors to tailor the content to their curriculum. Whether exploring generalized linear models, mixed-effects models, or dependent data analysis, students will gain a deep understanding of statistical methods and their applications across various domains. By the end of the book, readers will be equipped to make informed decisions, quantify uncertainty, and communicate their findings effectively.This book is not just a learning tool-it's a practical companion for aspiring data scientists seeking to master statistical practice and R programming.
