9780367698744 - statistical practice for data science: with hands-on illustrations using r de ravishanker, nalini; gopalakrishnan, asha; bar, haim (8 resultados)
- Tapa blanda
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 75,95
Envío por EUR 7,58Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
- Tapa blanda
Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 78,64
Envío por EUR 18,67Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
- Tapa blanda
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 88,31
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
- Tapa blanda
Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 99,81
Envío por EUR 3,46Se envía dentro de Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
Statistical Practice for Data Science
Nalini Ravishanker (University of Connecticut, Storrs, USA)|Asha Gopalakrishnan|Haim Bar
- Tapa blanda
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 74,59
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: 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.
- Tapa blanda
- Impresión bajo demanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 83,74
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fieldsengineering, science, and the biological, physical, and social scienceswith 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 toolits a practical companion for aspiring data scientists seeking to master statistical practice and R programming. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Tapa blanda
- Impresión bajo demanda
Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 91,84
Envío por EUR 18,67Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Tapa blanda
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 90,09
Envío por EUR 43,15Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fieldsengineering, science, and the biological, physical, and social scienceswith 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 toolits a practical companion for aspiring data scientists seeking to master statistical practice and R programming. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
