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Related Experiment Videos

Are accidents poisson distributed? A statistical test

A Nicholson1, Y D Wong

  • 1Department of Civil Engineering, University of Canterbury, Christchurch, New Zealand.

Accident; Analysis and Prevention
|February 1, 1993
PubMed
Summary
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This study reexamines the Poisson distribution assumption in accident count analysis. A more accurate combinatorial test shows the Poisson model is suitable for analyzing accidents at individual sites.

Area of Science:

  • Traffic Safety
  • Statistical Modeling
  • Transportation Engineering

Background:

  • Accident count analysis commonly assumes a Poisson distribution.
  • This assumption's validity, especially for small counts, requires rigorous evaluation.

Purpose of the Study:

  • To reexamine the suitability of the Poisson distribution for accident count data.
  • To compare the accuracy of statistical tests for evaluating this assumption.

Main Methods:

  • Description and comparison of two statistical tests: a chi-square test and a combinatorial analysis test.
  • Application of the more accurate test to reanalyze accident count variability data.

Main Results:

  • The combinatorial analysis test is significantly more accurate than the chi-square test for small accident counts.

Related Experiment Videos

  • Reanalysis of data supports the appropriateness of the Poisson distribution for individual site accident analysis.

    • Conclusions:

    • The Poisson distribution is a valid model for accident counts at individual sites.
    • A combinatorial test offers superior accuracy for evaluating this assumption with small datasets.