The book “Practicing R for Statistical Computing” is designed to provide a comprehensive introduction to R language for data presentation, manipulation, and statistical data analysis. The book covers fundamentals of data structures in R language such as vectors, matrices, arrays, and lists, along with techniques for exploratory data analysis, the transformation of the data, and its manipulation. The book explains basic statistical concepts and demonstrates their implementation 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 available in R.
Practicing R for Statistical Computing
The book also covers flow control and conditional computation using ‘if’ conditions and loops. A useful discussion is also done about 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 procedures, and adjustment of parameters are also explained. Throughout the book, R commands, functions, and objects are printed in different fonts for understanding and easy identification. The possible standard errors, warnings, and mistakes by users in the R language are also discussed and classified, and explanations on how to prevent them are given.
Chapter-wise downloadable R code files from Practicing R for Statistical Computing are:
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 6: Descriptive Statistics
Chapter 7: Probability and Probability Distributions
Chapter 8: Confidence Intervals and Comparison Tests
Chapter 9: Correlation & Regression Analysis
Chapter 11: Control Flow: Selection and Iteration
Chapter 12: Functions and R Resources
Chapter 13: Common Errors and Mistakes
Chapter 14: Functions for Better Programming
Chapter 15: This chapter lists the widely used built-in functions (No R code exists)
Chapter 16: This chapter lists several important R packages (No R code exists)
Authors:
Muhammad Aslam is Professor in the Department of Statistics at Bahauddin Zakariya University,
Muhammad Imdad Ullah is an Assistant Professor in the Department of Statistics at Ghazi University,
Muhammad Aslam is a Professor at the Department of Statistics at Bahauddin Zakariya University, Multan, Pakistan. He holds a Ph.D. in Statistics, a Master’s 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 Aslam’s 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 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 an 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 packages—mctest, lmridge, and liureg —and 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.
