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 example, you could use Jarque Bera test, see there. But, in almost all cases you should reject the null hypothesis despite that you see bell-shaped distribution of your data. The reason is that usual tests are quite sensitive to the big samples. Solution of this problem is using qq plot and histograms with choosing certain bins. Also, read this useful discussion.
