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A nonparametric approach to assess undergraduate performance

机译：评估本科性能的非参数方法

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摘要

Nonparametric methodologies are proposed to assess college students' performance. Emphasis is given to gender and sector of high school. The application concerns the University of Campinas, a research university in Southeast Brazil. In Brazil college studies are based on a somewhat rigid set of subjects for each major. For this reason a simple GPA comparison may hide true performance. Therefore,we define individual vectors of course grades. These vectors are used in pairwise comparisons of common subject grades for individuals who entered college in the same year. The relative college performances of any two students are compared with their relative performances on the entrance exam score. A procedure based on generalizedU-statistics is developed to test if there is selection bias in the entrance exam by some predefined groups, which is equipped with asymptotically normal distribution under both null and alternative hypotheses. Maximum power is attained by employing the union intersection principle, and resampling techniques such as nonparametric bootstrap are employed to generate the empirical distribution of the test statistics and get p-values.
机译：提出了非参数方法来评估大学生的表现。重点是高中的性别和部门。该申请涉及巴西东南部的研究大学坎皮纳斯大学。在巴西学院学习基于每个专业的一系列刚性的对象。因此，简单的GPA比较可能隐藏真正的性能。因此，我们定义了当地等级的个别向量。这些载体用于同年进入大学的个人的共同主题等级的成对比较。任何两个学生的相对大学表演都与入学考试评分的相对表演进行了比较。开发了一种基于通知统计数据的过程，以测试某些预定义组的入学考试中是否有选择偏差，其在空白和替代假设下配备有渐近正态分布。通过采用联盟交叉原理实现最大功率，并且采用诸如非参数引导拖放的重采样技术来生成测试统计的经验分布并获取p值。

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