| A GENERALLY APPLICABLE METHOD OF STATISTIC ANALYSIS FOR STUDYING AND CLASSIFYING NERVE TYPES OF CHILDREN,JUVENILES AND YOUTHS |
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| 作者姓名： | 陈荣昭 陈庆云 |
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| 作者单位： | [1]SuzhouInstituteofUrbanConsfructionandEnvieronmentolProtection [2]苏州大学数学系 |
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| 摘 要： | In this paper, a method of statistic analysis is suggested for studying and classifying nerve types of children, juveniles and youths. First, a set of effective calculating formulae is established so as to describe nerve types quantitatively. Thus, our analysis of nerve types is based on the experimental data. Since these data can not be considered as normally distributed, even the sampling is sized greatly. This has caused certain difficulties in the data analysis. The Box-Cox Transformation is proposed for the sampling data in this paper. As a result, direr tronsformation all the sets of experimental data can successfully pass Kolmogorov‘s no rmallsation test. And then, the suitable representative points in normal distribution are sleeted as classifying standards. Once the dividing points for classification are set up, the problem of classifying nerve types is solved successfully.
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| 关 键 词： | 统计分析 儿童 青少年 神经类型 |
A GENERALLY APPLICABLE METHOD OF STATISTIC ANALYSIS FOR STUDYING AND CLASSIFYING NERVE TYPES OF CHILDREN, JUVENILES AND YOUTHS |
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| Chen Rongzhao Suzhou Institute of Urban Construction and Environmental Protection Chen Qingyun Mathematics.A GENERALLY APPLICABLE METHOD OF STATISTIC ANALYSIS FOR STUDYING AND CLASSIFYING NERVE TYPES OF CHILDREN,JUVENILES AND YOUTHS[J].Journal of Suzhou University(Natural Science),1991,7(2):115-124. |
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| Authors: | Chen Rongzhao Suzhou Institute of Urban Construction and Environmental Protection Chen Qingyun Mathematics |
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| Institution: | Chen Rongzhao Suzhou Institute of Urban Construction and Environmental Protection Chen Qingyun Mathematics Department |
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| Abstract: | In this paper, a method of statistic analysis is suggested for studying and classifying nerve types of children, juveniles and youths. First, a set of effective calculating formulae is established so as to describe nerve types quantitatively. Thus, our analysis of nerve types is based on the experimental data. Since these data can not be considered as normally distributed, even the sampling is sized greatly. This has caused certain difficulties in the data analysis. The Box-Cox Transformation is proposed for the sampling data in this paper. As a result, after transformation all the sets of experimental data can successfully pass Kolmogorov's no rmalisation test. And then, the suitable representative points in normal distribution are slected as classifying standards. Once the dividing points for classification are set up, the problem of classifying nerve types is solved successfully. In fact, the method proposed in this paper is generally applicable. |
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| Keywords: | classification Box-cox Transformation representative point |
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