st: Testing normality of a continuous predictor variable in a logistic model

[Brendan <hsct@icon.co.za>]

I am working with a dataset containing 30000 observations. Some of  
the explanatory variables are continuous. If I perform usual tests  
for normality the numbers are too great for swilk or for sfrancia,  
and if I use sktest the result is "absurdly" large values and rejects  
the hypothesis of normal distribution. The frequency histogram,  
cumulative frequency plot and normal plot all look normal with no  
outliers. I presume that with such large numbers even very small  
deviations from normal will lead to a significant result. The box- 
tidwell test indicates that the model relationship is linear for all  
these continuous variables. Is it safe to ignore the sktest results?
Regards
Brendan
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