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背景:人体是1个不规则的几何体,难于对其体积进行测量。目的:建立以身高、体质量为自变量,人体体积为因变量的多种回归方程。进行大学男生身体体积计算模型的优选。设计:单一样本单因素分析。对象:于2003-01/2004-10选择浙江工商大学18～22岁男生共24名为观察对象。方法:测量男生的身高、体质量和身体体积。身高、体质量指标的测量均采用国家认定的体质测试仪器进行测量。身体体积指标采用自制的直径为0.95m、高为1.20m的铁容器,容器内安装1个有高度的刻度标记,将水灌入一定的高度,让学生慢慢地完全浸入水中,记录其高度差测量结果。人体体积穴m3雪=穴0.95÷2雪2×3.14159×高度差。进行测量数据的统计计算。以身高、体质量为自变量,以人体体积为因变量,运用体育科研数据统计处理系统软件包,建立二元回归方程,并完成回归方程的优选。主要观察指标:学生身高、体质量和身体体积测量数据与各种回归方程的计算结果。结果:①建立计算人体体积的二元回归方程:y=0.00616+0.000022×身高+0.000756×体质量。②人体体积的一元回归方程及方程的优选:线性方程为y=0.0008×体质量+0.0092;对数方程为y=0.0508ln穴体质量雪-0.1524;乘幂方程为y=0.0018×体质量0.8409;指数方程为y=0.0258×e0.0126x;复相关系数R2=0.9921～0.9973,均比较接近1,说明模型预测的人体体积值与实际的人体体积值呈高度相关眼r>r0.001穴24-2雪熏P<0.001演;4种模型预测值与实际值无差异。③从测量和计算的简便性分析,在5种回归方程中,线性方程最优。④人体体积指标与体质系列指标呈高度相关的指标涵盖身体形态、身体机能和身体素质指标。结论:人体体积指标在体质研究中是不可忽视的重要指标之一。从测量、计算的简便性和方程线性的拟合度分析,一元线性回归方程最优。^^^^^
Background: The human body is an irregular geometry that makes it difficult to measure its volume. Objective: To establish a variety of regression equations with height, body mass as independent variables and body volume as dependent variable. University boys body volume calculation model optimization. Design: Single sample univariate analysis. PARTICIPANTS: Twenty-four male subjects aged 18-22 years from Zhejiang Gongshang University were selected as observers from January 2003 to October 2004. Methods: The male height, weight and body mass were measured. Height, body mass index measurements using the national test of physical fitness equipment to measure. Body volume indicators made of homemade 0.95m diameter, 1.20m high iron container, the container installed a highly marked scale, the water poured into a certain height, so that students slowly fully immersed in water, record the height Poor measurement results. Human body volume hole snow snow = hole 0.95 ÷ 2 snow 2 × 3.14159 × height difference. Carry out statistical calculation of the measurement data. Taking height and body weight as independent variables and human body volume as dependent variable, the system software package of statistical data of sports scientific research was used to establish the binary regression equation and to complete the regression equation optimization. MAIN OUTCOME MEASURES: Student Height, Body Mass and Body Volume Measurement Data and Calculation Results of Various Regression Equations. Results: (1) To establish a binary regression equation for calculating body volume: y = 0.00616 + 0.000022 × height + 0.000756 × body mass. (1) The linear equation is y = 0.0008 × body mass +0.0092; the logarithmic equation is y = 0.0508ln The hole body mass snow -0.1524; The power equation is y = 0.0018 × The body mass is 0.8409 ; The exponential equation is y = 0.0258 × e0.0126x; the complex correlation coefficient R2 = 0.9921 ~ 0.9973, which are all close to 1, indicating that the model predicted body volume value is highly correlated with the actual body volume value eye r> r0.001 24 -2 snow smoked P <0.001; no difference between predicted and actual values of the 4 models. ③ From the convenience of measurement and calculation, the linear equation is the best among the five regression equations. ④ body mass index and physical series indicators are highly related indicators covering body shape, body function and physical fitness indicators. Conclusion: Body mass index is one of the most important indicators that can not be ignored in physical study. From the measurement, the simplicity of calculation and the linearity of the equation, the univariate linear regression equation is the best. ^^^^^