Quantitative Analysis and Interpretation of Big Data Variables in Crime Using R
Anupama Jha, Meenu Dave, Supriya Madan · International journal of advanced research in computer science and electronics engineering · 2016
The term Big Data is used to describe massive amount of data that arecharacterized by 5 V’s i.e. Volume, Variety, Velocity, Value and Veracity. Big data analysis is currently becoming increasingly important due to the exponentially growth of data generated in various fields such as Health care, Crime analysis, GIS etc. and the use of connected devices likelaptops, desktop computer, mobile phones and tablets. The large size and complexity of datasets in Big Data need sophisticated statistical tools for analysis where R System provides multiple dimensions to statistical analysis of dataset.This paper explores the analysis of different kinds of Big data variables such as categorical and quantitative implemented to Big Data in Crime domain using the statistical tool R. To implement statistical analysis, Crime dataset from the Maryland’s open data portal for the last 5 years have been downloaded. We explore the statistical analysis using different features of R i.e from data generation to visualization of the crime dataset. These statistical inferences can be used to analyze and identify the crime patterns to reduce further occurrences of similar type of incidence.