This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R.
Author(s): Muhammad Aslam; Muhammad Imdad Ullah
Publisher: Springer Nature Singapore
Year: 2023
Language: English
Pages: 292
Cover
Front Matter
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
