Safety Incidents - a Statistical Analysis

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Performance of Safety Incidents

Statistical Analysis of Safety Incident Rates

Table of Contents


Part I. Graphical Descriptive Statistics3
Part II. Binomial Probability Distribution4
Part III. Inferential Statistics5
Part IV. One Sample Hypothesis T-test5
Part V. Two Sample Hypothesis T-test6
Part VI. Paired (matched) Observation – Two Populations Hypothesis6 Part VII. Linear Regression and Correlation Study7
Part VIII. ANOVA – One-Way Test of Variance7
Part XI. Chi-square Goodness-of-Fit Test7
Part X. Chi-square Independence Test7

Appendix A:9

The measurement of safety performance is a hot topic in most companies today. Safety performance measurements seek to answer such questions as how do we compare to others? Are we getting better or worse over time? Is our management of safety effective (doing the right things)? Safety differs from many areas measured by managers because success results in the absence of an outcome (injuries or ill health) rather than a presence. As the scope of safety is vast, many stakeholders who are not safety professionals do not see safety as in such a broad way. They see “no injury” as good and “injury” as bad and that where it ends. This is one reason why incident rates and worker’s compensations costs have moved their way to the forefront of safety metrics. As an employee of a Facilities Engineering Command (a federal agency), working in the Operations Division, my role as an analyst requires me to gather and review metrics. Our safety metrics are very important to our organization as the safety and health program is dedicated to establishing a safety conscious culture throughout the command, ensuring that safe facilities are designed and constructed, ensuring that facilities and equipment are maintained in a safe, operating condition, eliminating facility, public works, and contact-related injuries and illnesses. In this paper will...
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