I am going to use the Kolmogorov-Smirnov test to test normality of MYDATA in R. This is an example of what I do

`ks.test(MYDATA,"pnorm",mean(MYDATA),sd(MYDATA))`

Here is the result R gives me:

`data: MYDATA D = 0.13527, p-value = 0.1721 alternative hypothesis: two-sided Warning message: In ks.test(MYDATA, "pnorm", mean(MYDATA), sd(MYDATA)) : ties should not be present for the Kolmogorov-Smirnov test`

I think there is a problem, what does “ties” mean in this warning?

**Answer**

You have two problems here:

The K-S test is for a continuous distribution and so MYDATA should not contain any ties (repeated values).

The theory underlying the K-S test does not let you estimate the parameters of the distribution from the data as you have done. The help for ks.test explains this.

**Attribution***Source : Link , Question Author : unes , Answer Author : mdewey*