Statistical Inference and Machine Learning for Big Data

This book presents a variety ofadvanced statistical methods ata level suitable foradvanced undergraduate and graduate students as well as for others interested in familiarizing themselves withthese important subjects. It proceeds toillustrate these methods in thecontext ofreal-life applications in a variety of areas such as genetics, medicine, and environmental problems. Thebook begins in Part I byoutlining various data types and byindicating how these are normally represented graphically and subsequently analyzed. In Part II, thebasic tools in probability and statistics are introduced with special reference to symbolic data analysis. Themost useful and relevant results pertinent tothis book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented. This book would serve as a handy desk reference forstatistical methods attheundergraduate and graduate level as well as be useful in courses which aim toprovide an overview ofmodern statistics and its applications.