Research on Physical Fitness Indicators of College Students Based on Bayesian Quantile Regression
To comprehensively investigate and comprehend the current state of physical fitness among college students,as well as the interplay between various physical indicators.A pioneering application of Bayesian quantile regression is introduved focused on the physical fitness index of university students in the year 2020.Firstly,correlation tests and significance assessments are conducted on these physical indicators.Sec-ondly,quadratic Bayesian quantile fitting is applied to data exhibiting robust correlations.The findings re-veal that the proposed quantile regression models offer superior fits for relationships,such as vital capacity and stature,50 m sprint and standing long jump for females,50 m sprint and Men's 1 000 m,50 m sprint and standing long jump for males,as well as Men's 1 000 m and the overall score.And model accuracy is best when quantile=0.25.The results demonstrate that Bayesian quantile regression can reflect the physical characteristics of college studentscomprehensively,and has higher detection accuracy and better robustness.
Bayesian quantile regressionsports statisticsphysical fitnesscollege students
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