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Full Description
Implementing R for Statistics provides comprehensive coverage of basic statistical concepts using this important open-source programming language tool, from installing R and RStudio, to exploring its basic structure and uses, to extending some core functions such as vectors, basic mathematical operations, and data frames. The book will help readers understand the latest advances in the R programming language, as R allows for sophisticated and elegant data visualization. Illustrated examples are an integral part of the text, carefully designed to apply the core principles illustrated in the text to emerging topics in the field.
The text also focuses on exploiting the flexible and user-friendly nature of R. Basic concepts and recent advances in the field, including understanding the R basics, as well as implementing and practicing them in statistics, are also covered. This first edition is an essential text for students, lecturers, data scientists, and applied researchers in all areas of statistics, as well as in related fields such as biostatistics, health care, finance, risk management, social sciences, market research, and environmental and climate research.
Contents
1. Crystal Symmetry
2. RStudio: A Quick Overview
3. R Fundamentals
4. Central Location and Dispersion Measures
5. Essentials to Model Fitting
6. Discrete Probability Distributions
7. Time Series Analysis
8. Regression and Correlation
9. Creating R Package: A Minimal Example
10. The Metadata: An Overview
11. Creating R Package: A moderate Level
