• The text is written in simple and lucid language.
• Every topic has been supplemented with underlying algorithms and illustrative programs as a better aid to understanding the basics.
• Each chapter has end-of-chapter exercises for the students to test their understanding of concepts.
• Each chapter is rich in pedagogy and includes figures, tables, and solved examples that supplement the topics discussed
• Introductory programming to students with a solid foundation in the R programming language is provided.
• Recent advances in this field for practicing professionals are detailed.
• All lab exercises in this book are thoroughly tested and the output is also shown on the console.

Unit I

Chapter 1 – Introduction to R Programming

1.1 What is R?

1.2 Physiognomies of R

1.3 Installing and Running R

1.4 R Sessions

1.5 R Environment

1.6 Historical Developments

1.7 Advantages of using R

1.8 Disadvantages of using R

Chapter 2 – Hands-On R Coding

2.1 Vectors in R

2.2 Functions in R

2.3 Advanced Data Structures

2.4 Basic Math

Chapter 3 – R Programming Structures

3.1 Constant

3.2 Variable

3.3 Expressions

3.4 Reserved Words in R

3.5 Data Types in R

Unit II

Chapter 4 – Operators in R

4.1 Introduction

4.2 R Arithmetic Operators

4.3 R Relational Operators

4.4 R Logical Operators

4.5 R Assignment Operators

4.6 Operators Precedence and Associativity

Chapter 5 – Control Statements in R

5.1 Introduction

5.2 Sequential Statements

5.3 Branching or Decision-Making Statements

5.4 Looping or Iterative Statements

5.5 Control Statements

Chapter 6 – Functions in R

6.1 Introduction

6.2 Return Value from a Function

6.3 Function without Return

6.4 Multiple Returns

6.5 Recursion

6.6 Quicksort

6.7 Binary Search Tree

Chapter 7 – Strings in R

7.1 Introduction

7.2 Rules for Constructing Strings in R

7.3 Rules for Manipulating Strings

Chapter 8 – Matrices in R

8.1 Introduction

8.2 Creating Matrices

8.3 Accessing Elements of Matrices

8.4 Matrix Computations

8.5 Matrix Addition and Subtraction

8.6 Matrix Multiplication and Division

Unit III

Chapter 9 – Math and Simulation

9.1 Introduction

9.2 Math Functions

9.3 Extended Example: Calculating a Probability

9.4 Cumulative Sums and Products

9.5 Minima and Maxima

9.6 Calculus

9.7 Statistics Based Distribution Functions

9.8 Sorting

9.9 Linear Algebraic Operations: Vectors and Matrices

9.10 Extended Example: Vector Cross Product

9.11 Extended Example: Finding Stationary Distribution of Markov Chains

9.12 The Set Operations

9.13 Simulation Programming in R

Chapter 10 – Input/Output in R

10.1 Introduction

10.2 Accessing the Keyboard and Monitor

10.3 Reading and Writing Files

Unit IV

Chapter 11 – Charts and Graphs in R

11.1 Introduction

11.2 R Bar Plot

11.3 Histograms

11.4 Pie-Chart

11.5 R Box Plot

11.6 Strip Chart in R

Chapter 12 – R Color

12.1 Introduction

12.2 Specifying Color Names

12.3 Using Hex Values

12.4 The RGB Values

12.5 Color Cycling

12.6 Color Palette

Chapter 13 – Plot Functions in R

13.1 Introduction

13.2 Titles and Labelling Axes

13.3 Changing Color and Plot Type

13.4 Overlaying Plots

13.5 Multiple Plots

13.6 Save Plots to File

Unit V

Chapter 14 – Probability Distributions and Basic Statistics

14.1 Qualitative Data

14.2 Frequency Distribution of Qualitative Data

14.3 Quantitative Data

14.4 Frequency Distribution of Quantitative Data

14.5 Cumulative Frequency Distribution

14.6 Numerical Measures

14.7 Standard Deviation

14.8 Covariance

14.9 Correlation Coefficient

14.1 Hypothesis Testing

14.11 Probability Distributions

Unit VI

Chapter 15 – Linear Models in R

15.1 Introduction

15.2 Fitting a Model

15.3 Simple Linear Regression

15.4 Multiple Regression

15.5 Generalized Linear Model

15.6 Logistic Regression

15.7 Poisson Regression

15.8 Other Generalized Linear Models

15.9 Survival Analysis

15.10 Non-Linear Models in R

A.K. Verma

A.K. Verma is currently working as Associate Professor in the Department of Computer Science and Engineering at Thapar University, Patiala. He received his PhD in 2008 specialising in Computer Science and Engineering. He has worked as Lecturer at M.M.M. Engineering College, Gorakhpur, from 1991 to 1996. He has been a visiting faculty to many institutions. Dr Verma has published over 150 papers in national and international journals and conferences. He is a certified software quality auditor by MoCIT, Govt of India. Prof. Verma’s research interests include wireless networks, routing algorithms, mobile computing, and securing ad hoc networks.