How to check for normal distribution in R if you have more than 5000 values (alternatives to shapiro-wilk or ks-test)? I m trying to check my data normal_data for normal distribution in R.
I always used shapiro.test or ks.test, but now I have more than 5000 values to check.
Is there any other function or possibility to check the data?

For the question in the title, see How to perform a test using R to see if data follows normal distribution  which gives many possibilities.  As for why the limitations of the Shapiro-Wilk test, see Can a sample larger than 5,000 data points be tested for normality using shapiro.test by applying the test to a subsample?
Then, (as mentioned by many in comments), why do you do this? See Testing large dataset for normality - how and is it reliable?   and   Is normality testing 'essentially useless'?
