Buch, Englisch, 420 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 762 g
Buch, Englisch, 420 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 762 g
ISBN: 978-1-032-77281-3
Verlag: Taylor & Francis Ltd (Sales)
The book provides a foundational guide to statistical computing and visualisation Using R programming with an emphasis on practical data analysis skills that are directly applicable to diverse fields like finance, defence, health, and education. It uniquely combines a thorough explanation of basic constructs with advanced topics such as data visualisation, statistical modeling, and probability, making it accessible yet comprehensive for learners across disciplines. This approach allows readers not only to build essential R skills but also to apply them to real-world scenarios, equipping students and professionals from various disciplines with versatile analytical tools. It offers a comprehensive yet approachable introduction for students and scholars from various disciplines using R.
- Includes practical and interactive elements such as quizzes, coding exercises, and hands-on projects can provide an engaging and effective learning experience for readers
- Provides complete code solutions to every problem presented, including detailed answers to even the most complex questions
- Presents case studies that can help contextualize the concepts covered in the book by showing how they are used in specific industries, fields, or contexts
- Offers application-based practical data analysis with cases in various fields and sectors, such as finance, healthcare, and marketing
- Focuses on best practices and efficient coding techniques, improving productivity and maintainability of R code
Zielgruppe
Academic, Postgraduate, and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik EDV | Informatik Technische Informatik Grid-Computing & Paralleles Rechnen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Objektorientierte Programmierung
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
Weitere Infos & Material
1. Introduction to R 2. R Programming Concepts 3. Data Structures in R 4. String Handling in R 5. Data Import and Export 6. Data Visualization 7. Real-World Applications