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.
The book also covers flow control and conditional calculations by using if conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.
Chapter
1. R Language: Introduction.
Chapter
2. Obtaining and
Installing R Language.
Chapter
3. Using R as a Calculator.
Chapter
4. Data
Mode and Data Structure.
Chapter
5. Working with Data.
Chapter
6.
Descriptive Statistics.
Chapter
7. Probability and Probability
Distributions.
Chapter
8. Confidence Intervals and Comparison Tests.-
Chapter
9. Correlation & Regression Analysis.
Chapter
10. Graphing in R.-
Chapter
11. Control Flow: election and Iteration.
Chapter
12. Functions and
R Resources.
Chapter
13. Common Errors and Mistakes.
Chapter
14. Functions
for Better Programming.
Chapter
15. Some Useful Functions.
Chapter
16.
Important Packages.
Muhammad Aslam is Professor at the Department of Statistics in Bahauddin Zakariya University, Multan, Pakistan. He holds a Ph.D. in Statistics, a Masters degree in Statistics, and a Post-Graduate Diploma in Computer Programming and Computing Statistics from the same university. He also completed his Post-Doctorate from the Institut de Mathematiques de Bourgogne, Dijon, France. Professor Aslams research is mainly focused on regression analysis and statistical inference, with a particular interest in simulation studies using computer programming. With more than 25 years of teaching experience, he has published more than 120 research articles in several prestigious international journals. Nine research scholars have successfully completed their Ph.D. degrees under his guidance. Muhammad Imdad Ullah, the co-author of this book, is among these scholars.
Muhammad Imdad Ullah is Assistant Professor at the Department of Statistics, Ghazi University,Dera Ghazi Khan, Pakistan. He received his Ph.D. degree from Bahauddin Zakariya University. He has also earned a Post-Graduate Diploma in Computer Programming and Computing Statistics. His Ph.D. work is about the development of R packages addressing linear regression models with the issue of multicollinearity. This work led to the development of three R packagesmctest, lmridge and liuregand three research articles based on these packages were published in The R Journal. His area of expertise includes computer programming and statistical computations. With over 14 years of teaching experience, he has authored 11 research publications.
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