European Journal of Statistics and Probability (EJSP)

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Empirical Analysis on Road Traffic Crashes in Anambra State, Nigeria: Accident Prediction Modeling Using Regression Approach

Abstract

Road traffic crashes in Anambra State Nigeria was considered in this paper, secondary data were mainly used, and was sourced from the office of the Federal Road Safety Corps; Policy, Research and Statistics Department RSHQ Abuja. Regression Analysis was applied on the data, with the aim of identifying how well a set of independent variables (Mechanical Fault, Reckless Driving and Over-Loading) is able to predict Road Accident in Anambra State, indicating, the best predictor of Road Accident in the state, knowing if Overloading is still able to predict a significant amount of the variance in Road Accident when Mechanical Fault and Reckless Driving is controlled for and to develop an accident prediction model. The result shows no violation to the assumptions of Normality, Homoscedasticity, Independence, Linearity, Multicollinearity and Outliers. The three predictors significantly predicted road accident { F(3,9) = 14.132, p-value =0.001 < 0.005 }, R2adjusted= 0.767; 76.7% , of the total variance in road accident cases was explained by the model, Mechanical Fault made the strongest unique significant contribution to explaining road accident cases when the variance explained by all other variables in the model  is controlled for (βeta value = 0.841, p-value = 0.001), Reckless driving made less of a contribution (βeta value =0.591, p-value = 0.004), while overloading did not make a significant contribution to the prediction of road accident when the variance explained by other variables in the model is controlled for (βeta value = 0.173, p-value = 0.228). The developed prediction model is; Number of Road Accident = 6.407 + 1.300Reckless Driving + 1.959Mechanical Fault + 0.733Overloading

Keywords: Anambra State, Empirical Analysis, Nigeria; Accident Prediction Modeling, Regression Approach, Road Traffic Crashes

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Email ID: submission@ea-journals.org
Impact Factor: 6.90
Print ISSN: 2055-0154
Online ISSN: 2055-0162
DOI: https://doi.org/10.37745/ejsp.2013

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