Statistic of occupational accident is an important index of occupational safety and health status. Government needs to compile statistic of occupational accident, forecast that establish policy and appraise outcome. Study makes use of multivalent statistical analysis and Time Series of correlation and regression to study between labor inspection and Occupational accident. The statistic model can bargain policy about preventing occupational accident.Result of statistic analysis has shown high inverse correlation between 1,000 rate of occupational fatality and safety and health inspection (correlation coefficient -0.906; p < 0.001). Another comparison with the manufacturing and construction industry, Founding that the construction industry needs more by means of safety and health inspection to achieve the purpose about preventing occupational accident. The power curve passes through logarithmic change and slope is 0.38 and 0.15, to result that inspection of construction industry is better than inspection of manufacturing. The result of autocorrelation analysis has found that the 1,000 rate of occupational fatality has autocorrelation, can further study reason what is industry of high autocorrelation of occupation accident. Another result of cross autocorrelation analysis has found that cross correlation between 1,000 rate of occupational fatality and safety and health inspection, can bargain about duplicate time of inspection.
Statistic of occupational accident is an important index of occupational safety and health status. Government needs to compile statistic of occupational accident, forecast that establish policy and appraise outcome. Study makes use of multivalent statistical analysis and Time Series of correlation and regression to study between labor inspection and Occupational accident. The statistic model can bargain policy about preventing occupational accident.Result of statistic analysis has shown high inverse correlation between 1,000 rate of occupational fatality and safety and health inspection (correlation coefficient -0.906; p < 0.001). Another comparison with the manufacturing and construction industry, Founding that the construction industry needs more by means of safety and health inspection to achieve the purpose about preventing occupational accident. The power curve passes through logarithmic change and slope is 0.38 and 0.15, to result that inspection of construction industry is better than inspection of manufacturing. The result of autocorrelation analysis has found that the 1,000 rate of occupational fatality has autocorrelation, can further study reason what is industry of high autocorrelation of occupation accident. Another result of cross autocorrelation analysis has found that cross correlation between 1,000 rate of occupational fatality and safety and health inspection, can bargain about duplicate time of inspection.
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