Uni- and bi-variate distribution

Example The yearly accident and near-accident summary report of an aluminium plant displays results of various uni- and bi-variate distribution analyses, including ... 

Uni- and bi-variate distributions give an overview of the accidents and help prioritisation in relation to in-depth analyses and in selecting remedial actions. Figure 15.5 shows another illustrative example. Here, the analysis identifies the energy types involved in the accidents in different departments of an offshore installation. 

Results of uni- and bi-variate distribution analyses are often used as proof of causal relationships. Let us look at two examples. We have earlier quoted a study that shows that 88 per cent of the accidents are caused primarily by unsafe acts (Heinrich, 1959). This statement is based on an uni-variate analysis of accidents by immediate cause. In the example in Section 15.2, an univariate distribution analysis showed that inattention was the cause of almost a quarter of the accidents. These examples bring us to the basic questions about what we mean by an accident cause. 

These analyses employ coded data. Results are displayed in tables, histograms, etc., showing the distribution of the accidents/near accidents in absolute number or percentage. Uni-variate analyses show the distribution of one variable and bi-variate analyses display cross-tables of two variables. This is a well-established data-analysis method employed in companies periodical statistical summaries of accidents and near accidents. 

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