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Is it true that that ${{n}\choose{k}} p^k (1-p)^{n-k}$ is dominated by $\frac{1}{n}$, at least for $k$ sufficiently big?

EDIT: I saw that the question was absolutely not stated as I intended. The real question is: given a real number $p \in (0, 1)$, assuming $k$ fixed big enough, is there some constant $C > 0$ independent from $k$ such that $n \cdot {{n}\choose{k}} q^k (1-q)^{n-k} \leq C$ for every $n \geq k$?

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  • $\begingroup$ No: set $k=n>1$ and $p=1$. $\endgroup$ Commented Jan 29, 2017 at 19:45
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    $\begingroup$ And if p < 1, with k fixed? $\endgroup$
    – John K
    Commented Jan 29, 2017 at 19:50
  • $\begingroup$ Can you explain more clearly what the question is? I am confused about what is fixed and what varies. Furthermore, the question you ask is now answered, so you should really edit the question rather than changing it in the comments. Edit: hopefully Robert has made the right assumptions about what the question actually is. $\endgroup$ Commented Jan 29, 2017 at 19:53
  • $\begingroup$ k is a fixed natural number, n varies, p is a real number in (0, 1). $\endgroup$
    – John K
    Commented Jan 29, 2017 at 19:55
  • $\begingroup$ OK then it looks like Robert's answer does it. $\endgroup$ Commented Jan 29, 2017 at 19:56

3 Answers 3

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Robert's answer is correct, if you want an asymptotic answer. However, for the question as stated in the edit (that is for all $n\ge k$...) the answer is no.

Take for example the case of $p=\frac12$. For any $k$, if you take $n=2k$ then ${n \choose k}p^k(1-p)^{n-k}=\frac{(2k)!}{k!k!2^{2k}}$ which is roughly $\frac{1}{\sqrt{\pi k}}$ by Stirling's formula. This is, of course, bigger then $\frac{1}{n}$.

The same also works for other values of $0<p<1$ by taking $n=k/p$.

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Assuming $0 \le p \le 1$, $n$ and $k$ nonnegative integers with $n \ge k$, ${n \choose k} p^k(1-p)^{n-k} = \mathbb P(X = k)$ where $X$ is a binomial random variable with parameters $n$ and $p$ (i.e. the number of successes in $n$ independent Bernoulli trials with probability $p$ of success in each).

I think you want to take $n \to \infty$ with fixed $k$. Of course, if $p = 0$ or $p=1$ the probability is $0$ for $1 \le k \le n-1$, so let's suppose $0 < p < 1$. Now ${n \choose k}$ is a polynomial in $n$, while $(1-p)^{n-k}$ decays exponentially, and therefore faster than any negative power of $n$. Thus it is true that $\mathbb P(X=k) < 1/n$ for sufficiently large $n$.

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Say $k=np$ (imagine $p=1/2$), then that is about $C/\sqrt{n}$ for some constant $C$. This is by (for example) a normal approximation to the underlying binomial random variable, or (perhaps more to the point) recognizing that the binomial random variable has standard deviation about $C\sqrt{n}.$

This ($1/\sqrt{n}$) is the biggest the sum gets. If $|k-np|/\sqrt{n}$ is much larger than 1, then this expression really really quickly falls to $0$. (See many different bounds for this, but perhaps just bound it by the normal approximation.)

You may find useful the bounds $(n/k)^k \leq {n \choose k} \leq (en/k)^k,$ which almost always help clear things like this up considerably.

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