Statistical Predictive Modelling through R Programming

This book is to work on various modelling predictive analysis for statistical data and graphical presentation through R programming. R is major tool implemented in statistical research as well as used in many applications like banking, insurance, healthcare and in business analytics that contains large datasets of hidden patterns. It performs handling data, displaying data and storing data by using set of arithmetic operations over matrices and arrays. To handle data R programming creates data structures. In chapter1, the author describes the need of analytics in different sectors and specific areas of R programming. In Chapter2, the author describes R installation and process of working using basic Math functions, operations and by generating classes. In chapter3, the author describes different control statements in R programming by handling functions and examples for sorting techniques. In chapter4, the author describes the perception of math and simulation for professional statistics based on distribution functions. Key concepts for reading and writing files through accessing files from keyboard and monitor. In chapter5, the author describes solving procedures for statistical problems using probability distributions, basic statistic functions, correlation and covariance. In chapter6, the author describes various implementations of regressions models through linear and non-linear models by loading R packages and installations. In chapter7, the author describes graphical use of statistics through R and real-time examples for business analytics and bank using R clustering performing k-means.