看一下我这张图. 图像看起来非常符合正态分布。
SAS output结果如下:
Parameter Symbol Estimate
Mean Mu 0.467856
Std Dev Sigma 0.193649
Goodness-of-Fit Tests for Normal Distribution
Test ---Statistic---- -----p Value-----
Kolmogorov-Smirnov D 0.01143319 Pr > D <0.010
Cramer-von Mises W-Sq 0.30026701 Pr > W-Sq <0.005
Anderson-Darling A-Sq 3.10816502 Pr > A-Sq <0.005
Quantiles for Normal Distribution
------Quantile------
Percent Observed Estimated
1.0 0.04494 0.01736
5.0 0.14636 0.14933
10.0 0.21098 0.21968
25.0 0.33080 0.33724
50.0 0.46982 0.46786
75.0 0.59886 0.59847
90.0 0.72291 0.71603
95.0 0.79499 0.78638
99.0 0.89970 0.91835
KS对应的P-value这么小. P<0.01.
可是如果按照SAS Help里面写的
The Kolmogorov-Smirnov D statistic, the Anderson-Darling statistic, and the Cramér-von Mises statistic are based on the empirical distribution function (EDF). However, some EDF tests are not supported when certain combinations of the parameters of a specified distribution are estimated. See Table 3.62 for a list of the EDF tests available. You determine whether to reject the null hypothesis by examining the p-value that is associated with a goodness-of-fit statistic. When the p-value is less than the predetermined critical value (), you reject the null hypothesis and conclude that the data did not come from the specified distribution.
如果设定 0.05的置信标准,那就应该认为该分布不符合正态分布了。
是不是我的理解有问题,为什么p值这么小?