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1、对体力测试(共7项指标)及运动能力测试(共5项指标)两组指标进行典型相关分析Run MATRIX procedure:Correlations for Set-1X1 X2 X3 X4 X5 X6 X7X1 1.0000 .2701 .1643 -.0286 .2463 .0722 -.1664X2 .2701 1.0000 .2694 .0406 -.0670 .3463 .2709X3 .1643 .2694 1.0000 .3190 -.2427 .1931 -.0176X4 -.0286 .0406 .3190 1.0000 -.0370 .0524 .2035X5 .2463 -.0670 -.2427 -.0370 1.0000 .0517 .3231X6 .0722 .3463 .1931 .0524 .0517 1.0000 .2813X7 -.1664 .2709 -.0176 .2035 .3231 .2813 1.0000Correlations for Set-2X8 X9 X10 X11 X12X8 1.0000 -.4429 -.2647 -.4629 .0777X9 -.4429 1.0000 .4989 .6067 -.4744X10 -.2647 .4989 1.0000 .3562 -.5285X11 -.4629 .6067 .3562 1.0000 -.4369X12 .0777 -.4744 -.5285 -.4369 1.0000两组变量的相关矩阵说明,体力测试指标与运动能力测试指标是有相关性的。Correlations Between Set-1 and Set-2X8 X9 X10 X11 X12X1 -.4005 .3609 .4116 .2797 -.4709X2 -.3900 .5584 .3977 .4511 -.0488X3 -.3026 .5590 .5538 .3215 -.4802X4 -.2834 .2711 -.0414 .2470 -.1007X5 -.4295 -.1843 -.0116 .1415 -.0132X6 -.0800 .2596 .3310 .2359 -.2939X7 -.2568 .1501 .0388 .0841 .1923上面给出的是两组变量间各变量的两两相关矩阵,可见体力测试指标与运动能力测试指标间确实存在相关性,这里需要做的就是提取出综合指标代表这种相关性。Canonical Correlations1 .8482 .7073 .6484 .3515 .290上面是提取出的5个典型相关系数的大小,可见第一典型相关系数为0.848,第二典型相关系数为0.707,第三典型相关系数为0.648,第四典型相关系数为0. 351,第五典型相关系数为0. 290。Test that remaining correlations are zero:Wilks Chi-SQ DF Sig.1 .065 83.194 35.000 .0002 .233 44.440 24.000 .0073 .466 23.302 15.000 .0784 .803 6.682 8.000 .5715 .916 2.673 3.000 .445上表为检验各典型相关系数有无统计学意义,可见第一、第二典型相关系数有统计学意义,而其余典型相关系数则没有。Standardized Canonical Coefficients for Set-11 2 3 4 5X1 .475 .115 .391 -.452 -.462X2 .190 -.565 -.774 .307 .489X3 .634 .048 .288 .321 -.276X4 .040 .080 -.400 -.906 .422X5 .233 .773 -.681 .459 .233X6 .117 .148 .425 .141 .649X7 .038 -.394 .025 -.103 -1.029Raw Canonical Coefficients for Set-11 2 3 4 5X1 .141 .034 .116 -.134 -.137X2 .026 -.076 -.104 .041 .066X3 .040 .003 .018 .020 -.018X4 .008 .015 -.075 -.169 .079X5 .016 .054 -.047 .032 .016X6 .020 .025 .071 .024 .109X7 .005 -.048 .003 -.013 -.126上面为各典型变量与变量组1中各变量间标化与未标化的系数列表,由此我们可以写出典型变量的转换公式(标化的)为:L1=0.475X1+0.19X2+0.634X3+0.04X4+0.233X5+0.117X6+0.038X7余下同理。Standardized Canonical Coefficients for Set-21 2 3 4 5X8 -.505 -.659 .577 .186 .631X9 .209 -1.115 .207 -.775 -.292X10 .365 -.262 .188 1.153 -.154X11 -.068 -.034 -.579 .340 1.181X12 -.372 -.896 -.649 .569 -.124Raw Canonical Coefficients for Set-21 2 3 4 5X8 -1.441 -1.879 1.647 .531 1.798X9 .005 -.026 .005 -.018 -.007X10 .133 -.095 .069 .419 -.056X11 -.018 -.009 -.153 .090 .312X12 -.012 -.029 -.021 .018 -.004Canonical Loadings for Set-11 2 3 4 5X1 .689 .235 .099 -.150 -.112X2 .526 -.625 -.408 .225 .237X3 .741 -.212 .263 -.042 .001X4 .242 -.032 -.298 -.809 .182X5 .200 .705 -.558 .257 -.161X6 .364 -.096 .191 .224 .476X7 .115 -.259 -.437 .053 -.471Cross Loadings for Set-11 2 3 4 5X1 .584 .166 .064 -.053 -.032X2 .446 -.442 -.265 .079 .069X3 .629 -.150 .170 -.015 .000X4 .205 -.023 -.193 -.284 .053X5 .170 .498 -.362 .090 -.047X6 .309 -.068 .124 .079 .138X7 .098 -.183 -.283 .019 -.136上表为第一变量组中各变量分别与自身、相对的典型变量的相关系数,可见它们主要和第一对典型变量的关系比较密切。Canonical Loadings for Set-21 2 3 4 5X8 -.692 -.149 .654 .111 .244X9 .750 -.550 .001 -.346 .127X10 .776 -.183 .275 .538 .020X11 .585 -.108 -.371 -.054 .711X12 -.674 -.265 -.548 .193 -.371Cross Loadings for Set-21 2 3 4 5X8 -.587 -.106 .424 .039 .071X9 .636 -.389 .001 -.121 .037X10 .658 -.129 .178 .189 .006X11 .496 -.076 -.240 -.019 .206X12 -.571 -.187 -.355 .068 -.108上表为第二变量组中各变量分别与自身、相对的典型变量的相关系数,结论与前相同。下面即将输出的是冗余度(Redundancy)分析结果,它列出各典型相关系数所能解释原变量变异的比例,可以用来辅助判断需要保留多少个典型相关系数。 Redundancy Analysis:Proportion of Variance of Set-1 Explain
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