인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
학술저널
DBpia Top 5%
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
Objective: This study aims to contribute to the examination of causes considering trends and the establishment of comprehensive industrial accident prevention measures by comparing the characteristics and types of accidents by major industrial groups and analyzing the main characteristics of accidents that occurred over the past 10 years.
Background: Korea is faced with various industrial accidents, and the Korea Occupational Safety & Health Agency (KOSHA) conducts an industrial accident survey every year to produce statistical data related to various industrial accidents. However, since the report is mainly composed of technical statistical analysis, it is difficult to conduct an in-depth analysis for the prevention of industrial accidents. In particular, the year-by-year comparison of accident victims that occur every year is simple, so various analyses from a time series perspective are insufficient. Therefore, in order to conduct a more comprehensive analysis of industrial accidents and establish preventive measures, research that compares and analyzes them from various perspectives is also necessary.
Method: Data on fatalities by industry type and accident type over the past 10 years (2014-2023) were collected, and cross-analysis using the Chi-square Test was performed to confirm the significance of each type by year. And since occupational diseases among the types of disasters are provided as separate detailed data, we additionally checked the significance of the yearly differences. In addition, during this analysis process, it was determined that there was a difference in the number of deaths between 2022 and 2023, so we conducted a statistical verification of this difference. And we explained the meaning of each result.
Results: We analyzed the statistical significance of the relationship between the number of deaths each year for 10 years by industry type and disaster type using a categorical cross-analysis based on the Pearson chi-square test, and confirmed that there was a difference by type. There was a difference between the last two years (2022 and 2023), but there was no statistically significant difference.
Conclusion: This study analyzed various influencing factors that can affect industrial accident fatalities and the relationships and meanings between those factors.
Background: Korea is faced with various industrial accidents, and the Korea Occupational Safety & Health Agency (KOSHA) conducts an industrial accident survey every year to produce statistical data related to various industrial accidents. However, since the report is mainly composed of technical statistical analysis, it is difficult to conduct an in-depth analysis for the prevention of industrial accidents. In particular, the year-by-year comparison of accident victims that occur every year is simple, so various analyses from a time series perspective are insufficient. Therefore, in order to conduct a more comprehensive analysis of industrial accidents and establish preventive measures, research that compares and analyzes them from various perspectives is also necessary.
Method: Data on fatalities by industry type and accident type over the past 10 years (2014-2023) were collected, and cross-analysis using the Chi-square Test was performed to confirm the significance of each type by year. And since occupational diseases among the types of disasters are provided as separate detailed data, we additionally checked the significance of the yearly differences. In addition, during this analysis process, it was determined that there was a difference in the number of deaths between 2022 and 2023, so we conducted a statistical verification of this difference. And we explained the meaning of each result.
Results: We analyzed the statistical significance of the relationship between the number of deaths each year for 10 years by industry type and disaster type using a categorical cross-analysis based on the Pearson chi-square test, and confirmed that there was a difference by type. There was a difference between the last two years (2022 and 2023), but there was no statistically significant difference.
Conclusion: This study analyzed various influencing factors that can affect industrial accident fatalities and the relationships and meanings between those factors.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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