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Analysis of Experimental Data Using Discriminants, Ellipsoidal Contours, and Hotelling's T2

机译：使用判别式，椭圆形轮廓和Hotelling的T2分析实验数据

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align="left">This paper focuses on the Multivariate Analysis of Variance (MANOVA), a method widely used in the biosciences. Engineers involved in experimental work can find linear discriminants, ellipsoidal? contours, and Hate/ling's P test useful when they compare two groups of experiments that differ by some criteria. With ellipsoidal contours, they can visualize the approximate extent of the distribution of? the data in each group. With Hate/ling 's T2 test, they can determine whether the differences between the groups are occurring by more than chance. With linear discriminant functions, they can define? a model to determine the membership of a data point to a group. Such a model is referred to as a classifier. Two numerical examples are? presented with the use of graphical illustrations. The first example? explains the presentation of the three methods. The second example utilizes experimental data on pull-out tests of prestressing strands.
机译：align =“ left”>本文重点介绍了在生物科学中广泛使用的方差多元分析（MANOVA）。从事实验工作的工程师可以找到线性判别式，椭圆形吗？等高线和Hate / ling的P检验在比较两组按某些标准不同的实验时很有用。利用椭圆形轮廓，它们可以可视化分布的大致程度？每个组中的数据。通过Hate / ling的T2测试，他们可以确定组之间的差异是否偶然发生。使用线性判别函数，它们可以定义？用于确定组的数据点的成员资格的模型。这种模型称为分类器。两个数值示例是？使用图形插图呈现。第一个例子？解释了这三种方法的介绍。第二个例子利用了预应力钢绞线拉拔试验的实验数据。

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