Practicing R for statistical computing

1. R Language: Introduction 2. Obtaining and Installing R Language 3. Using R as a Calculator 4. Data Mode and Data Structure 5. Working with Data 6. Descriptive Statistics 7. Probability and Probability Distributions 8. Confidence Intervals and Comparison Tests 9. Correlation and Regression Analysis 10. Graphing in R 11. Control Flow: Selection and Iteration 12. Functions and R Resources 13. Common Errors and Mistakes 14. Functions for Better Programming 15. Some Useful Functions 16. Important Packages

This book offers a comprehensive introduction to R programming for data analysis, manipulation, and presentation. It covers fundamental data structures like vectors, matrices, arrays, and lists, as well as techniques for exploratory data analysis, transformation, and manipulation. The book explains basic statistical concepts, including descriptive statistics, graphical representation, probability, and hypothesis testing. It also covers linear and non-linear modeling, model selection, and diagnostic tools in R. The book also covers flow control, conditional calculations, and useful functions for further learning. It also covers the use of different graphic devices and parameter adjustments.