摘要
χ2(m)分布与F(m1,m2)分布的密度函数的图像都是只取非负值的偏态分布,而且二者密度函数图像类似,因此二者的分布函数以及经验分布函数的图像也同样类似.对于一组来自χ2(m)分布或F(m1,m 2)分布的数据,用通常的作经验分布函数图像的方法,难以区分这组数据到底来自哪一个总体.提出了用假设检验的方法判断一组来自χ2(m)分布或F(m1,m2)分布数据是服从χ2(m)分布还是服从F(m1,m 2)分布.
The image of x^2 distribution＇s density function and F distribution＇s density function are the skewness distribution of non-negative member. However, the image of the two density function are similar, so the images of their distribution function and empirical distribution function are similar too. For a group of data collected from x^2 distribution or F distribution, it is difficult to judge where they are from if use the usual way of making image about empirical distribution function. Proposed a scientific method of the hypothesis testing to distinguish F distribution and x^2 distribution .
出处
《高师理科学刊》
2008年第3期33-35,共3页
Journal of Science of Teachers＇College and University
关键词
Χ^2分布
F分布
假设检验
x^2 distribution
F distribution
hypothesis testing
