Ramalingam Shanmugam,
Texas State University, USA
Title: Correlation and distance concepts together suggest impaired driving due to alcohol than marijuana is menace to road safety
Biography
Biography: Ramalingam Shanmugam,
Abstract
Sometimes, repeated experience with accidents makes people to believe and conclude that impaired driving due to alcohol or marijuana is menace to road safety. However, policy makers on road safety require data evidence authenticated interpretations. What statistical methodologies now exist to do so to help policy makers? For this purpose, this exploratory and tutorial article is written with data analyses and interpretations of actual number of fatal accidents caused by impaired driving during 2013-2015 in USA (as reported in Arnold and Teft 2016). This research work first convinces, using regression analysis, that the driver’s age is not a significant predictor of fatal accidents. Then, in a novel manner, it mixes correlation and Mahalanobis distance concepts to create an approach to check whether impaired driving due to alcohol or marijuana is a serious menace to the road safety. In conclusion, this research work finds that just by eliminating impaired drivers due to alcohol (but not marijuana) could ensure road safety 16.02 times closer to an ideal situation of no fatal road accident