May 1, 2024
3 minute read
**Hierarchical data** is a data structure that represents a hierarchy of elements. A hierarchy is an arrangement of elements in which each element has a superior element, except for the top-level element. For example, a company's organizational chart is a hierarchical data structure, with the CEO at the top, followed by vice presidents, directors, managers, and employees. Other examples of hierarchical data include file systems, XML documents, and relational databases with parent-child relationships.
Why Learn About Hierarchical Data?
There are many reasons why you might want to learn about hierarchical data. Here are a few:
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Find a path to becoming a Hierarchical Data. Learn more at:
OpenCourser.com/topic/6qpr68/hierarchical
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Hierarchical Data.
Written by two pioneers in the field of hierarchical linear modeling, this book provides a comprehensive introduction to the topic, covering both theory and applications.
Explores the use of hierarchical models in environmental science, providing real-world examples and case studies.
Provides a thorough treatment of probability and statistical inference, which are essential foundations for understanding hierarchical models.
Provides a practical introduction to Bayesian hierarchical modeling using the R programming language.
While not specifically focused on hierarchical data, this classic work provides a comprehensive treatment of Bayesian data analysis, including hierarchical modeling.
Provides a thorough treatment of mixed effects models, a type of hierarchical model that is widely used in various fields.
Includes a chapter on hierarchical Bayesian models, providing an introduction to the topic from a machine learning perspective.
While not specifically about hierarchical data, this book provides a strong mathematical foundation for understanding the theory behind hierarchical models.
Includes a chapter on hierarchical clustering, a type of hierarchical model used for unsupervised learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/6qpr68/hierarchical