Introduction to Statistical Computing and Visualization Using R

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A01=Megha Rathi
Applied Data Analysis
Author_Megha Rathi
Category=GPJ
Category=UB
Category=UFM
Category=ULR
Category=UMB
Category=UMX
Category=UMZ
Category=UYF
coding exercises for students
Data Visualization
data wrangling techniques
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
interactive R programming projects
Machine Learning
multivariate analysis
Predictive analytics
probability theory applications
Programming in R for Data Science
quantitative research methods
Sports analytics
Statistical Computing
statistical modelling case studies

Product details

  • ISBN 9781032772813
  • Weight: 940g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Apr 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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

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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