Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science: Series Number 6 (Institute of Mathematical Statistics Monographs, Series Number 6)
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Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science: Series Number 6 (Institute of Mathematical Statistics Monographs, Series Number 6)
This book delivers a concentrated course in modern statistical thinking
Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science: Series Number 6 (Institute of Mathematical Statistics Monographs, Series Number 6)
Preces #: 194111164

Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science: Series Number 6 (Institute of Mathematical Statistics

Preces #: 194111164

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Shop Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science: Series Number 6 (Institute of Mathematical Statistics Monographs, Series Number 6) online at a best price in Latvia. 1108823416
  • Presents a concentrated course in modern statistical thinking with a distinctly modern approach
  • Covers influential topics such as survival analysis, logistic regression, empirical Bayes, random forests, and more
  • Integrates methodology and algorithms with statistical inference
  • Includes class-tested exercises at the end of each chapter
  • Speculates on the future direction of statistics and data science
  • Available in a paperback edition and fortified with exercises
Publisher Cambridge University Press
Publication date 17 Jun. 2021
Edition Student
Language English
Print length 512 pages
ISBN-10 1108823416
ISBN-13 978-1108823418
Item weight 1.05 kg
Dimensions 15.24 x 2.95 x 22.86 cm

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Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science: Series Number 6 (Institute of Mathematical Statistics Monographs, Series Number 6)

About This Item

Get ahead in the world of data science and statistical inference with the "Computer Age Statistical Inference, Student Edition." This comprehensive book, a part of the Mathematical Statistics Monographs Series Number 6, delves into algorithms, evidence, and data science methodologies. Perfect for students and researchers alike, this book delves into statistical methods, data analysis techniques, and statistical computing for comprehensive learning. Whether you are a part of the Data Science Institute or simply interested in the field, this book is a valuable resource.

It has received rave reviews from experts and scholars and is a great addition to any collection focusing on data interpretation, theory, and research. Take your knowledge further and dive into the world of predictive modeling, machine learning, and statistical research as you unlock the potential of data science. Don't miss out on this essential addition to your learning journey.

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Data Mining Editorial Review

Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, And Data Science: Series Number 6 (Institute Of Mathematical Statistics Monographs, Series Number 6) offers a comprehensive exploration of statistical inference in the context of data science. With a published date of June 17, 2021, this student edition provides insights into contemporary algorithms and evidence-based methodologies that are crucial for understanding data science. The text, spanning 512 pages, is well-structured, making it accessible for students. Additionally, the book's emphasis on algorithms aligns with current trends in statistical applications, making it a valuable resource for students aiming to enhance their analytical skills.

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Pros

  • Published by renowned Cambridge University Press
  • Comprehensive content on statistical inference
  • User-friendly structure for easy comprehension
  • Covers contemporary algorithms and methodologies
  • Well suited for data science students

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  • The book may be extensive for some readers.

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Funkcijas un priekšrocības

  • Explores the expansion of statistical methodology in the 21st century
  • Focuses on modern statistical thinking and integrates it with methodology and algorithms
  • Includes chapters on influential topics such as survival analysis, neural networks, and inference after model selection
  • Fortified with exercises and class-tested exercises

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