Consider the following basic random walk : $S_n=\sum_{k=1}^n X_k$ where the $(X_k)$ are i.i.d. with $P(X_k=(-1))=P(X_k=1)=\frac{1}{2}$. Let $M_n=\max(0,S_1,S_2, \ldots ,S_n)$ and $\mu(n,t)=P(M_n \leq t)$.
Using the reflection principle , (as explained here), and putting $q=\lfloor \frac{n-1}{2} \rfloor$ one can see that
$$ \mu(n,t)=P\bigg( -2\lfloor \frac{t}{2} \rfloor-1\leq S_{2q+1} \leq 2\lceil \frac{t}{2} \rceil-1\bigg)=\frac{1}{2^{2q+1}} \sum_{j=-\lfloor \frac{t}{2} \rfloor}^{\lceil \frac{t}{2} \rceil} \binom{2q+1}{q+j} \tag{1} $$
The Stirling formula yields $\binom{2q+1}{q+j} \sim_{q \to \infty} \frac{2^{2q+1}}{\sqrt{\pi q}}$ for any $j$, and hence for a fixed $t$,
$$ \mu(n,t) \sim_{n\to \infty} (t+1) \sqrt{\frac{2}{\pi n}} \tag{2} $$
I ask if this limit is also an uniform upper bound, in the sense that
$$ \mu(n,t) \leq (t+1) \sqrt{\frac{2}{\pi n}} \text{ whenever } \ \mu(n,t) \ \text{is not trivial (i.e. equal to } 0 \ \text{ or } \ 1). \tag{3} $$
UPDATE 02/14/2013 I’ve just realized that the two-variables inequality (3) follows from the much simpler one-variable inequality
$$ \frac{\binom{2q+1}{q}}{2^{2q+1}} \leq \sqrt{\frac{1}{\pi (q+1)}} \tag{4} $$
Indeed, the numerator in the RHS of (1) is a sum of $t+1$ binomials, and the largest such binomial is $\binom{2q+1}{q}$. So (1) implies that
$$ \mu(n,t) \leq (t+1) \frac{\binom{2q+1}{q}}{2^{2q+1}} \tag{5} $$
Inequality (4) looks much easier to prove.