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Categorical Data Analysis and Multilevel Modeling Using R
By Xing (Eastern Connecticut State University) Liu
CHF 124.00
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If you find the same book(s) cheaper (new, in stock, like-for-like including delivery), we’ll match it. Not applicable to international orders. Read the full policy.
Description
In Categorical Data Analysis and Multilevel Modeling Using R, Xing Liu offers a comprehensive exploration of advanced statistical techniques essential for researchers and practitioners in various fields. This meticulously crafted text delves into the complexities of categorical data analysis, providing a robust framework for understanding and applying multilevel modelling using the R programming language.
The Story
The book begins with fundamental concepts, gradually building towards more intricate methodologies. Liu’s clear explanations and practical examples guide readers through the intricacies of data analysis. The text is rich with real-world applications, enabling readers to grasp how these techniques can be employed across diverse research scenarios.
Why Readers Love It
- Clarity and Accessibility: Liu’s approachable writing style demystifies complex statistical theories, making them accessible to all readers.
- Practical Applications: Each chapter is replete with examples and exercises that encourage hands-on learning and application of the concepts discussed.
- Comprehensive Coverage: The book addresses a wide range of topics, from basic categorical data analysis to advanced multilevel modelling techniques.
Perfect For
This book is ideal for graduate students, researchers, and practitioners in fields such as social sciences, healthcare, and education who seek to enhance their understanding of data analysis methodologies. Those familiar with R will find it particularly beneficial, as it not only teaches the statistical techniques but also integrates them seamlessly with programming practices.
Overall, Liu's work is a valuable addition to the literature on statistical modelling, providing essential insights that are applicable in both academic and professional contexts.
Specifications
Format: Paperback / softback
Dimensions: × ×
Pages: 744
Publisher: SAGE Publications
ISBN: 9781544324906
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