Introduction to Statistical Computing and Visualization Using R

· CRC Press
El. knyga
420
Puslapiai
Tinkama
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Apie šią el. knygą

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

Apie autorių

Dr. Megha Rathi is currently serving as an Assistant Professor (senior grade) in the Department of Computer Science at Jaypee Institute of Information Technology (JIIT), Noida, India. She holds a Ph.D. in Computer Science from Banasthali University and has over fifteen years of experience in teaching and research. Throughout her career, Dr. Rathi has contributed significantly to various research areas, including sustainable computing, data mining, data science analytics, health science, and machine learning. She has worked on key projects, such as the Xform generator at the National Informatics Centre (NIC), Delhi, and has experience in software development through her role as a Project Associate at the Indian Institute of Technology (IIT), Delhi. She has been actively involved in organizing special sessions at international conferences and has delivered invited talks. Additionally, she has organized numerous FDP’s and workshops also guided numerous B.Tech/M.Tech/PhD students, playing a pivotal role in shaping their research and academic development.

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