Learn all about R (programming language for statistical computing and graphics)
R is a programming language and software environment designed for statistical computing and graphics. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand in the early 1990s. The name "R" is derived from the first letter of the names of its creators.
The eBook is in PDF format and costs $14.99
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The book covers the following topics:
1. Introduction to R
Brief history and development of R
Installing R and RStudio
Basic concepts and features of R
2. Getting Started with R
R syntax and basic operations
Variables, data types, and data structures in R
Working with vectors, matrices, and arrays
Introduction to data frames
3. Data Manipulation and Analysis
Importing and exporting data in R
Data cleaning and preprocessing
Exploratory data analysis
Data visualization using base R graphics and packages like ggplot2
4. Programming in R
Control structures (if-else, loops)
Functions and their usage
Error handling and debugging techniques
Writing efficient and readable code
5. Statistical Analysis with R
Descriptive statistics and summary measures
Hypothesis testing and statistical inference
Regression analysis (linear regression, logistic regression)
Time series analysis and forecasting
Multivariate analysis (clustering, factor analysis)
6. Advanced Topics in R
Object-oriented programming in R
Creating and using packages in R
Parallel computing and performance optimization
Web scraping and accessing APIs in R
7. R for Machine Learning
Introduction to machine learning concepts
Supervised learning (classification, regression)
Unsupervised learning (clustering, dimensionality reduction)
Model evaluation and selection
8. R for Big Data
Working with large datasets in R
Introduction to distributed computing frameworks (e.g., Spark)
Using R for big data analytics
9. R in Practice
Case studies and real-world examples
Best practices for R programming
Tips and tricks for efficient R usage
10. Resources and Next Steps
Additional learning resources (books, websites, online courses)
R community and support forums
Advanced topics and specialized packages
Future trends and developments in R
The eBook is in PDF format and costs $14.99
Please click here to buy the eBook.