How do you test polyserial randomness?

I´m using the 'Polyserial Correlation' from the 'Package polycor version 0.7-10' in R, to analyse my data (X=CMR_NDJF - continuous; Y=Total_Min - ordinal) and I'm obtaining good results.

X
  [1]           NA -1.344043226 -1.719367970 -0.592629307 -0.662019757  4.352661767
  .....


[181]  1.663420159
> Y
  [1] NA  "0" "0" "0" "0" "1" "0" "0" "1" "1" "0" "0" "1" "1" "1" "0" "1" "0" "0" "0"
 .....

[181] "1"

and I'm obtaining good results:

polyserial(X, Y, ML=TRUE, std.err=TRUE) # ML estimate


Polyserial Correlation, ML est. = 0.807 (0.03952)
Test of bivariate normality: Chisquare = 32.56, df = 5, p = 4.592e-06

                1
Threshold 0.59070
Std.Err.  0.07961

1. How can I verify if these results obtained with polyserial would be very different if my data ( X column) were random? I only find references to polychoric correlation random tests.

2. Is it possible to perform a random test analysis to polyserial correlation with an R package?