About author : Dr. Janardhan Kadari was Former Head Department of Biotechnology, AV College of Arts, Science and Commerce, Hyderabad. Former Head Department of Botany Bhavan’s New Science College, Narayanguda, Hyderabad. He Guided One Research Scholar as Co- Supervisor for Ph.D. and published around 30 research papers and gave invited Lectures. Also gave Video Lectures for Rajiv Gandhi University of knowledge Technologies. Attended National and International conferences and conducted workshops. Dr.janardhan kadari Attended spatial statistics workshop held by the Department of Statistics in Fort Collins, Colorado on April 10 & 11,2013. Dr.Janardhan also has published three text books for graduate and post graduate students in the area of Biotechnology, Biostatistics and Biomathematics.

About book : R is a Statistcal programming language. R is Free and open source. R is an interpreted language not a compiled one. The R programming environment contains the range of tools for parallel computing, machine and deep learning and for working with big Data, including Torch and Tensar flow facilitating construction and implementation of neural networks. The Bioconductor repository contains over a thousand of software packages written in R for analyzing data sets from CDNA microarrays to copy-number variation and epigenomics (Robert Gentleman-Sorin Draghicia). Due to Data Handling and Modeling capabilities and its flexibility, R is becoming the most widely used software in bioinformatics. The R program is built from a variety of packages. These packages are libraries of commands. The Packages are available from the CRAN website. The current R is the result of a collaborative effort of the R core Group. R has many functions for statistical analysis and graphics. R has an effective data handling and storage facility. R provides operators for calculation on arrays, vectors, lists and matrices. This Book Covers all these with suitable examples. R has a collection of tools for data analysis. Keeping in view the Beginners apprehensions the Book provides the Salient Features of Descriptive Statistics & Covers the specific R tools for Statistical analysis. Throughout the Book examples are accompanied by R commands for easy reference. This Book Covers data handling, graphics, and a wide range of Statistical techniques. The Book would be of immense help to basic sciences, Engineering, Business Statistics, medicine streams, Biotechnology, Pharma, Bioinformatics, Genetics and Epidemiology.