£94.31

Springer Statistical Learning and Modeling in Data Analysis Book

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Description

Expand your knowledge of data science with Statistical Learning and Modeling in Data Analysis: Methods and Applications. Published by Springer, this book provides a comprehensive look at modern methods for statistical learning and modeling. It serves as a valuable resource for understanding how to apply complex theories to real-world scenarios. The content covers a wide range of research topics, including statistical inference, modeling, clustering, and factorial methods. Readers can explore specialized areas such as directional data analysis, time series analysis, and small area estimation. By studying these peer-reviewed contributions, you gain insight into how these methods function across diverse industries. This book is designed to bridge the gap between theory and practice. It presents applications in critical fields such as medicine, finance, engineering, marketing, and cyber risk. Whether you are researching classification or knowledge organization, this collection offers selected research to help you master modern data analysis techniques.

Key Features

Covers modern statistical learning methods and modeling techniques for advanced data analysis.

Includes research on diverse topics like clustering, factorial methods, and statistical inference.

Explores specialized areas including time series analysis and small area estimation.

Provides real-world applications across medicine, finance, engineering, and marketing sectors.

Features peer-reviewed contributions focused on classification and knowledge organization.

Addresses specialized subjects such as directional data analysis and cyber risk modeling.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
14 July 2021
Listed Since
21 January 2021

Barcode

No barcode data available

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