  Analysis of road accidents is crucial to understand the factors involved and
their impact. Accidents usually involve multiple variables like time, weather
conditions, age of driver, etc. and hence it is challenging to analyze the
data. To solve this problem, we use Multiple Correspondence Analysis (MCA) to
first, filter out the most number of variables which can be visualized
effectively in two dimensions and then study the correlations among these
variables in a two dimensional scatter plot. Other variables, for which MCA
cannot capture ample variance in the projected dimensions, we use hypothesis
testing and time series analysis for the study.
