Data Reduction And Analysis

Data Reduction and Analysis examines various aspects of data analysis including brief overview of data environment. It starts with establishing a clear picture of statistics to data science with Python and R. It comprise concepts of data analysis and error analysis. Provides the reader with insights into the reduction and analysis of data in order to develop a deep understanding of given data. Additionally, includes appendices on SciPy for Statistics, Statistical Testing, and Pandas.

Dr. U. S. Raghavender did his Masters in Physics, with specialization in Condensed Matter Physics, followed by his doctoral thesis in X-ray Crystallography of Designed molecules. This was followed by post-doctoral stints in India and abroad, in both academic institutions and non-academic institutions. He has been working on computational approaches of biomolecules, since the past 12 years. He has authored book chapters, published research in internationally acclaimed journals. He also serves as a peer reviewer of research articles published in both national (Journal of Biosciences) and international journals (BMC Bioinformatics, Nucleic Acids Research etc.). He has a long term goal of addressing computational aspects of regulatory mechanisms in cell.