The formula
First, the formula I found for the odds of rolling at least one 1 when rolling an n-sided die n times:
Math.round(1 - ( ((n-1)/n)^n -1 )*(n^n-1) )/n^n
AKA:
Note: As n grows, the Math.round becomes less necessary.
Now, here's how I got there:
I started with the basics:
I then continued with the basics, but noticed some patterns:
In particular, I noticed that the number of outcomes that included at least one 1 could be determined from a sum that is based on the number of first 1's in a row, per column (note that the first 1's in each row are bolded in the above image, their counts shown at the bottom of each column, and that the non-first 1's in each row are made red):
I then recast the sum as a definite integral:
From there I used Wolfram to crank out an estimated solution for the number of outcomes that include at least one 1 (some hand-waving steps have been left out...because I don't remember them):
And bing-bang-boom, as long as I round that estimated number of outcomes containing at least one 1 before dividing it by the total number of outcomes (n^n), I got the right answer!
In closing
I don't think that this formula is better for computational solutions for the odds of getting at least one 1 when rolling an n-sided die n times -- because of the fast growing n^n... buuut, I do feel like this solution exposes some sort of potentially unique connection between the physical world and the realm of probabilities... admittedly, I'm not good at statistics and recognize that my googling skills may also have failed me when trying to find a similar analysis.
PS:
The leap I made to using summation notation came from my playing around with methods for representing the odds for different values of n using MS Excel. Please note that the appearance of "!" in the final image below denotes my joy at finding answers to the questions I'd posed in the first two of these final three images, not factorials.