In the testing of normality, how would the 2 compare? Is one significantly better than the other?
When should we apply normality tests? For which types of the variables should we apply the normality test? For example dependent variables, independent variables, or control variables, etc?
I'm currently looking for a test having for null hypothesis that the sample does not come from observing a normally distributed random variable. In other words, I'd like to know if there's a test ...
I have a program generating purportedly normal distributions and I would like to test it. I have a number of issues; perhaps the experts here will help me sort out the essential from the inessential ...
It is a general and maybe stupid question, but it will help me to avoid a mistake. To test the dependence of continuous variable on nominal with parametric test (t-test, ANOVA), "the data has to be ...
I have a sample size of 6. In such a case, does it make sense to test for normality using the Kolmogorov-Smirnov test? I used SPSS. I have a very small sample size because it takes time to get each. ...
Background: In connection with the question here I came upon a more interesting question. I believe the question is large and distinct enough to have it's own thread. Of course I might be mistaken, ...
A former colleague once argued to me as follows: "we usually apply normality tests to the results of processes that, under the null, generate random variables that are only asymptotically or nearly ...
Some guys told me that it's appropriate to use Wald-Wolfowitz Runs Test as a normality test (like Shapiro-Wilk's or Kolmogorov-Smirnov...). Do you think this is good way to test normality assumptions? ...
Title says enough... so far, I've been using Shapiro-Wilk's statistic in order to test normality assumptions in small samples. Could you, please, recommend another technique?