GRAPHICAL INSIGHT INTO MULTIPLE-REGRESSION CONCEPTS

被引:0
|
作者
FRANKLIN, LA
机构
来源
AMERICAN STATISTICIAN | 1992年 / 46卷 / 04期
关键词
GRAPHICS; MEAN SQUARE ERROR; MODEL SIGNIFICANCE; MULTICOLINEARITY; P-VALUES;
D O I
10.2307/2685314
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This article describes how pedagogical benefits can be achieved in the comprehension of (frequently) difficult multiple regression concepts by following Martin Gardner's injunction to simplify the problem. Specifically presenting the simplest multiple regression model (two independent variables) with the smallest nondegenerate data set (four points) and systematically changing the arrangement of the points, graphically one gains intuition into many important multiple regression concepts. These include the following: the size and determination of s2 = sigma2 , the size and meaning of R2, the significance of the overall regression model, the size and significance of each of the model's coefficients, multicolinearity, and how the location of the underlying data set influences each of these.
引用
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页码:284 / 288
页数:5
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