基于大数据的大学生体质健康测试数据分析及健康促进对策

Analysis of College Students'Physical Health Test Data Based on Big Data and Health Promotion Countermeasures

运用大数据分析技术将某大学2017~2019年所有在校学生体质健康的65535条记录为数据源,运用基于距离的聚类(K-means)算法,按男、女性别分类的两组数据进行聚类分析,并对一系列的数据进行处理、转换以及建模分析。结论:男生组各聚类的身体素质测试项目评分平均值变化趋势大体相近且变化缓和;女生组各聚类的身体素质测试项目评分平均值变化呈现了两个明显的谷底且变化趋势较为错综复杂。通过分析聚类结果发掘学生身体素质与指标之间的内在联系,进而提出了相对应的健康促进对策,以期全面提升学生的体质健康水平。

Using big data analysis technology,65535 records of physical health of all students in a university from 2017 to 2019 are taken as data sources.Using distance based clustering(K-means)algorithm,two groups of data classified by male and female are clustered,and a series of data are processed,transformed and modeled.Conclusion:the change trend of the average score of physical fitness test items in male group is similar and moderate,the change trend of the average score of physical fitness test items in female group shows two obvious bottoms and the change trend is complex.By analyzing the clustering results,this paper explores the internal relationship between students'physical fitness and indicators,and then puts forward the corresponding health promotion countermeasures,in order to comprehensively improve students'physical health level.