The number of times one needs to sample with replacement to cover a fraction P of a set Take the expression $(1-(1-\frac{1}{n})^x)$, which is the expected fraction of elements one samples from a set of $n$ elements, sampling with replacement (and uniform probability) $x$ times.  
Provided some $n$, how do we analytically solve for $x$ s.t. $(1-(1-\frac{1}{n})^x) \geq P$?  It appears that $\frac{x}{n}$ converges to a fixed value as $n \to \inf$.  Is this true?  If so, how do we find it without relying on numerical methods?

The inequality can be rewritten as
$$\left(1-\frac{1}{n}\right)^x\le 1-P.$$
We first solve the equation
$$\left(1-\frac{1}{n}\right)^t= 1-P.$$
Take the (natural) logarithm of both sides. 
We get
$$t\log\left(1-\frac{1}{n}\right)=\log(1-P).$$
Thus
$$t=\frac{\log(1-P)}{\log\left(1-\frac{1}{n}\right)}.$$
Presumably we want $x$ to be an integer. The smallest integer $x$ for which our inequality holds is $\lceil t\rceil$.
It is clear that $x\to \infty$ as $n\to\infty$. However, something interesting happens if we look at $\frac{x}{n}$. We look instead at the closely related $\frac{t}{n}$, which has the same limit. We have
$$\frac{t}{n}=\frac{\log(1-P)}{n\log\left(1-\frac{1}{n}\right)}.$$
Note that the denominator $n\log\left(1-\frac{1}{n}\right)$ is equal to 
$\log\left(\left(1-\frac{1}{n}\right)^n\right)$. But $(1-1/n)^n\to e^{-1}$ as $n\to\infty$, so the denominator approaches $-1$. It follows that as $n\to\infty$, $\dfrac{t}{n}$ (and therefore $\dfrac{x}{n}$) approaches $-\log(1-P)$. 
