寻求帮助和合作论文
<span id="post1" style="color: rgb(0, 0, 0); font-size: 12px;">我现在有一个问题寻求帮助和合作论文。<br/>是这样的，我想要分析的是y 和x
的关系（见附件），但是x和y好像是没有关系；然而，x和sum-y（就是y的累加）相关性却相当高(0.999)，根据由Excel得到的回归方程，回
归的sum-y与实测的sum-y误差也很小，但是回归的y
值（由回归的第n个sum-y减去实测的第n-1个sum-y得到）与原值就误差很大。我想请教一下，为什么会出现这个问题？能否通过数学方法来解决这个
问题（就是使回归的y值与原值误差尽量小）？ 此问题如果能够较好解决，可以合作发表数篇SCI文章。<br/> Email: <a href="mailto:shangbinx@163.com">shangbinx@163.com</a><br/><br/>xySum-ykb回归Sum-y回归yy误差Sum-y误差<br/>818.2991304318.2991304314.426-107.378.04 8.04 56.07 -56.07 <br/>98.28420289926.5833333314.426-107.3722.46 4.16 49.73 -15.50 <br/>1013.0194202939.6027536214.426-107.3736.89 10.31 20.84 -6.85 <br/>1110.7163768150.3191304314.426-107.3751.32 11.71 -9.30 1.98 <br/>1216.8469565267.1660869614.426-107.3765.74 15.42 8.45 -2.12 <br/>1318.3817391385.5478260914.426-107.3780.17 13.00 29.27 -6.29 <br/>1415.61869565101.166521714.426-107.3794.59 9.05 42.08 -6.50 <br/>1516.06550725117.23202914.426-107.37109.02 7.85 51.12 -7.00 <br/>168.746086957125.978115914.426-107.37123.45 6.21 28.95 -2.01 <br/>1713.05043478139.028550714.426-107.37137.87 11.89 8.86 -0.83 <br/>1816.7973913155.82594214.426-107.37152.30 13.27 21.00 -2.26 <br/>1918.08942029173.915362314.426-107.37166.72 10.90 39.75 -4.13 <br/>2012.67884058186.594202914.426-107.37181.15 7.23 42.94 -2.92 <br/>2114.95057971201.544782614.426-107.37195.58 8.98 39.92 -2.96 <br/>227.70826087209.253043514.426-107.37210.00 8.46 -9.72 0.36 <br/>2315.15101449224.40405814.426-107.37224.43 15.17 -0.16 0.01 <br/>249.017536232233.421594214.426-107.37238.85 14.45 -60.24 2.33 <br/>2515.5173913248.938985514.426-107.37253.28 19.86 -27.98 1.74 <br/>269.612898551258.551884114.426-107.37267.71 18.77 -95.23 3.54 <br/>2711.43463768269.986521714.426-107.37282.13 23.58 -106.22 4.50 <br/>289.68057971279.667101414.426-107.37296.56 26.57 -174.48 6.04 <br/>2915.69695652295.36405814.426-107.37310.98 31.32 -99.51 5.29 <br/>3023.96057971319.324637714.426-107.37325.41 30.05 -25.40 1.91 <br/>3111.25275362330.577391314.426-107.37339.84 20.51 -82.28 2.80 <br/>3217.30521739347.882608714.426-107.37354.26 23.68 -36.86 1.83 <br/>3320.73057971368.613188414.426-107.37368.69 20.81 -0.36 0.02 <br/>3414.03101449382.644202914.426-107.37383.11 14.50 -3.35 0.12 <br/>3511.49144928394.135652214.426-107.37397.54 14.90 -29.63 0.86 <br/>3613.13927536407.274927514.426-107.37411.97 17.83 -35.70 1.15 <br/>3717.4126087424.687536214.426-107.37426.39 19.12 -9.79 0.40 <br/>3812.16971014436.857246414.426-107.37440.82 16.13 -32.55 0.91 <br/>3917.73463768454.591884114.426-107.37455.24 18.39 -3.68 0.14 <br/>4012.85086957467.442753614.426-107.37469.67 15.08 -17.33 0.48 <br/>4116.75014493484.192898614.426-107.37484.10 16.65 0.58 -0.02 <br/>4212.93797101497.130869614.426-107.37498.52 14.33 -10.75 0.28 <br/>4313.13869565510.269565214.426-107.37512.95 15.82 -20.39 0.52 <br/>4413.86507246524.134637714.426-107.37527.37 17.10 -23.36 0.62 <br/>4514.03391304538.168550714.426-107.37541.80 17.67 -25.88 0.67 <br/>4621.87521739560.043768114.426-107.37556.23 18.06 17.45 -0.68 <br/>4714.13927536574.183043514.426-107.37570.65 10.61 24.97 -0.61 <br/>4818.02391304592.206956514.426-107.37585.08 10.89 39.55 -1.20 <br/>4911.22318841603.430144914.426-107.37599.50 7.30 34.98 -0.65 <br/>5016.23086957619.661014514.426-107.37613.93 10.50 35.31 -0.92 <br/>519.766666667629.427681214.426-107.37628.36 8.69 10.97 -0.17 <br/>5214.02217391643.449855114.426-107.37642.78 13.35 4.76 -0.10 <br/>5315.70492754659.154782614.426-107.37657.21 13.76 12.40 -0.30 <br/>5417.80811594676.962898614.426-107.37671.63 12.48 29.92 -0.79 <br/>5519.51333333696.476231914.426-107.37686.06 9.10 53.38 -1.50 <br/>5610.46217391706.938405814.426-107.37700.49 4.01 61.67 -0.91 </span> 什么问题 啊！
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