Mastering R: A Guide to the R Programming Language
by Vanita B
English | December 16, 2024 | ASIN: B0DQQDZD3N | 78 pages | PDF | 23 Mb
by Vanita B
English | December 16, 2024 | ASIN: B0DQQDZD3N | 78 pages | PDF | 23 Mb
"Mastering R: A Guide to the R Programming Language" is your comprehensive companion on the journey to mastering R, a powerful language widely used in data analysis, statistical computing, and data visualization. This guide is meticulously designed to cater to both beginners and advanced users, providing a structured and thorough exploration of R's capabilities.
What You Will Learn:
Introduction to R:
Understand the basics of R, including its history, features, and applications.
Learn how to install R and set up your development environment.
Basic R Programming:
Familiarize yourself with R syntax and data types.
Learn how to write and execute R scripts.
Understand and use vectors, lists, matrices, and data frames.
Data Manipulation:
Master the essential techniques for data cleaning and preprocessing.
Explore the dplyr and tidyr packages for efficient data manipulation.
Data Visualization:
Create stunning visualizations using the ggplot2 package.
Learn how to build a variety of charts, including line plots, bar charts, histograms, and scatter plots.
Statistical Analysis:
Conduct basic and advanced statistical analyses in R.
Learn about hypothesis testing, regression analysis, and ANOVA.
Machine Learning:
Get introduced to machine learning concepts and techniques in R.
Explore supervised and unsupervised learning algorithms using the caret and mlr3 packages.
Advanced R Programming:
Delve into advanced topics such as writing functions, error handling, and object-oriented programming in R.
Learn how to create and use packages to extend R's functionality.
Reproducible Research:
Understand the principles of reproducible research.
Learn how to use R Markdown to create dynamic reports and presentations.
Key Features:
Step-by-Step Tutorials: Follow detailed, step-by-step tutorials to build your R skills progressively.
Real-World Examples: Apply what you've learned to real-world datasets and scenarios.
Comprehensive Coverage: Cover all essential aspects of R, from basic programming to advanced techniques.
Hands-On Projects: Engage in hands-on projects that reinforce your learning and demonstrate practical applications.
Expert Insights: Benefit from expert tips and best practices for efficient R programming and data analysis.