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- Use R! Applied Spatial Data Analysis with R, Book 10, (Paperback)
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Nº de artículo:
152116511
Use R! Applied Spatial Data Analysis with R, Book 10, (Paperback)
Nº de artículo:
152116511
NIO 2691
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This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data.
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What Stands Out
Comprehensive Coverage
Covers a wide array of spatial data analysis techniques, ensuring readers have a thorough understanding of methodologies relevant to various applications in R.
Practical Examples
Includes hands-on examples and case studies, allowing readers to apply theoretical concepts in practical situations, enhancing learning and retention.
User-Friendly Guide
Written for both beginners and experienced users, the book simplifies complex topics, making spatial data analysis accessible without sacrificing depth or detail.
Detalles de producto
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Textbooks |
| Publication date | June, 2013 |
| Pages | 405 |
| Subgenre | Biostatistics |
| Series title | Use R! |
| Number in series | 10 |
| Edition | 2nd 2013 Edition |
| Publisher | Springer New York |
| Original languages | English |
| Language | English |
| Edu focus | Geography & Globes |
| Educational level | College |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.10 x 0.90 x 9.00 in (15.5 x 2.3 x 22.9 cm) |
| Assembled product weight | 1.2 lb (540 grams) |
| Bisac subject heading | Medical |
Who Should Buy?
-
Data Analysts
Professionals seeking to enhance their skills in spatial data analysis using R programming tools effectively.
-
Academics
Students or researchers in geography or environmental science looking for a practical guide to spatial data analysis.
-
GIS Professionals
Geographic Information System specialists looking to deepen their understanding of spatial statistics and R applications.
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Beginner Programmers
Users with no background in R or programming may struggle to grasp the concepts presented in the book.
DESCRIPCIÓN DEL PRODUCTO
Use R! Applied Spatial Data Analysis with R, Book 10, (Paperback)
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Preguntas y respuestas de los clientes
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Pregunta:
What is the primary focus of this book?
Respuesta: The book focuses on using R for handling, visualizing, and analyzing spatial data. -
Pregunta:
What types of data analysis methods are covered?
Respuesta: It covers standard methods and new developments, including point pattern analysis and disease mapping. -
Pregunta:
Is there additional support material available?
Respuesta: Yes, the book has a dedicated website with code examples, data sets, and other supportive materials.
Roger S Bivand All Books Editorial Review
Use R! Applied Spatial Data Analysis with R, Book 10, (Paperback) provides an in-depth exploration of biostatistics tailored for college-level learners. This second edition, published by Springer New York in June 2013, spans 405 pages and is structured to enhance understanding of spatial data analysis through the R programming language. Readers will appreciate its non-fiction content, focusing on educational themes related to geography and globes, making it ideal for students and professionals alike. The paperback format is lightweight and easy to handle, ensuring convenient use during studies or reference. Equipped with practical examples, this textbook is a great addition to any academic collection.
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ventajas
- Ideal for college-level education
- Effective for spatial data analysis
- Comprehensive coverage of biostatistics
- Published by a reputable academic publisher
- User-friendly paperback format
Contras
- Not suitable for beginners without prior statistical knowledge
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características y beneficios
- Provides comprehensive coverage of R packages for spatial data analysis.
- Includes data import/export for multiple spatial data formats.
- Covers specialized analysis techniques such as interpolation and geostatistics.
- Offers practical examples from spatial statistics literature.
- Features a systematic approach to spatial data handling in R.
- Suitable for various fields including geography, ecology, and public health.
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