不同样本量在stata中都采用什么方式检验正态分布

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大家好，
       现在我有几个样本，有样本量上万的，有在5000左右的，有1000多的，还有几十的，对于这样不同的样本量的样本，每一个在stata中检验是否正态分布的时候，各采用什么检验方法和检验语句啊？
       请高手解答下哦！知道一点点的大家也可以讨论下哈！

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关键词：Stata 正态分布 tata 样本量 检验方法 正态分布 样本 左右

Assume here you want to do the univariate analysis of normality test, I think the sample size matters only for different chioces of plots, the idea is the same. Check the attachment, it seems a good tutorial for your question.  

Bayesian.var 发表于 2011-10-18 23:10
Assume here you want to do the univariate analysis of normality test, I think the sample size matter ...

It seems very helpful

help normality gives you different normality tests

谢谢楼上的几位啊，我先试试哈！

谢谢分享。。。。

Bayesian.var 发表于 2011-10-18 23:10
Assume here you want to do the univariate analysis of normality test, I think the sample size matter ...

高手你好，
     我大概看了下这篇文献，在这篇文献的第八页，给出了各种方法的样本数范围，比如说Skewness-Kurtosis需要大于9，Shapiro-Wilk小于2000，Shapiro-Francia小于5000。Kolmogorov-Smirnov没有，就是说范围不限制了吧？在stata中help normal还可以找到Kolmogorov-Smirnov检验的公式。可在这篇文献中又有这样的一句话：
Stata .ksmirnov command is not used for testing normality.
所以我想问问您是怎么理解的？Kolmogorov-Smirnov应该还是可以进行正态性检验的吧？还是说它属于类似正态性检验？

thanks

cheerhappy 发表于 2011-10-25 09:08
高手你好，
     我大概看了下这篇文献，在这篇文献的第八页，给出了各种方法的样本数范围，比如说Ske ...

Hi,

Kolmogorov-Smirnov test was designed to compare two experimentally-determined distributions. When testing for normality, you compare an experimental distribution against a hypothetical ideal (Suppose the true normal distribution with mean mu and variance sigma, but both parameter mu and sigma you don't know), if you use Stata .ksmirnov, you may test it against normal like the example commands in (help ksmirnov),
webuse ksxmpl
summarize x
ksmirnov x = normal((x-r(mean))/r(sd))
which is using the sample mean r(mean) and the sample variance r(sd)^2 as the true parameters. By doing that the result of KS test will be conservative in the sense that it will be less likely to reject the null hypothesis, then you need to apply the Lilliefors correction which is not being done in .ksmirnov... In conclusion, Stata .ksmirnov command is not ready and so useful for testing normality. I recommend that you skip using the Kolmogorov-Smirnov test, and switch instead to the other alternative tests. But first rethink whether the normality tests are providing you with useful information.
      

Bayesian.var 发表于 2011-10-28 22:22
Hi,

Kolmogorov-Smirnov test was designed to compare two experimentally-determined distribution ...

Thanks， then if N>5000, which normality tests is better, ksmirnov(for one sample or two sample) or sktest? And could the test of ksmirnov apply to many more samples?