4
$\begingroup$

Given a binomial distribution with $n$ expeiments, where probability of success is $p$. $\text{prob}(x=k) = \binom{n}{k} p^k (1-p)^{n-k}$

I'm trying to show that for odd values of $n\geq 3$, $p > .5$, we always have:

$$ \text{prob}(x > n/2) > p $$

where $\text{prob}(x > n/2) = \sum_{k=\lfloor n/2 \rfloor+ 1}^n \binom{n}{k} p^k (1-p)^{n-k}$

What I tried: I tried to expand $(p + q)^n = 1$ where $q=1-p$, and argue the sum second half of the terms is greater than $p$. But other than the trivial case of $p=.5$, seems like my argument is not really useful.

I appreciate any help to prove or disprove this claim.

$\endgroup$
19
  • $\begingroup$ The claim is far from true. Just take $p$ sufficiently near $.5$ $\endgroup$
    – lulu
    Commented Dec 6, 2021 at 18:01
  • $\begingroup$ @lulu I cannot see thank, could you expand on the comment a little please. Also possible that I'm not explaining the problem properly. $\endgroup$
    – Alt
    Commented Dec 6, 2021 at 18:07
  • $\begingroup$ If $p$ is very small then the probability histogram of $X$ will be skewed right $\endgroup$
    – user801306
    Commented Dec 6, 2021 at 18:10
  • $\begingroup$ @lulu, I'm trying to proof or disprove that in distribution, probability of success of majority voting, is higher than success of an individual vote. $\endgroup$
    – Alt
    Commented Dec 6, 2021 at 18:10
  • 1
    $\begingroup$ @Thomas: For even $n$, a similar statement is true, when, in case of ties, one decides uniformly randomly between success and failure (note that if we require strict majority, the statement is not true, as for $n=2$, the probability of strict majority is $p^2<p$). I believe in that case we can use a similar argument as the one presented in my answer below. $\endgroup$ Commented Dec 7, 2021 at 13:11

2 Answers 2

4
$\begingroup$

I will slightly adapt notation for convenience. Denote $X_i \in \{-1,1\}$ i.i.d. Bernoulli random variables with $P(X_i=1) = p$ and $P(X_i=-1) = 1-p$, where $0.5<p<1$ and $S_n = \sum_{i=1}^nX_i$. Then we are proving $P(S_{2m+1}\geq 1)>p$ for all $m>0$.

To start with, notice that $S_{2m+1}$ only assumes odd integer values and $S_{2m+1}=S_{2m-1}+X_{2m}+X_{2m+1}$. Therefore, $S_{2m+1}\geq1$ precisely if either $S_{2m-1}>1$, or $S_{2m-1}=-1\land X_{2m}=X_{2m+1}=1$, or $S_{2m-1}=1\land X_{2m}+X_{2m+1}\geq0$. With this insight, we deduce the following recursive expressions \begin{align} P(S_{2m+1}\geq 1) &=P(S_{2m-1} >1) + P(S_{2m-1} = -1)p^2 + P(S_{2m-1} = 1)(1-(1-p)^2) \\ &=P(S_{2m-1} \geq 1) + P(S_{2m-1} = -1)p^2 - P(S_{2m-1} = 1)(1-p)^2, \end{align} where we used $P(S_{2m-1} >1)+P(S_{2m-1} =1)=P(S_{2m-1} \geq1)$. Inserting $P(S_{2m-1} = 1)(1-p) = P(S_{2m-1} = -1)p$ (which can be verified via evaluating the binomial distribution), we obtain $$ P(S_{2m+1}\geq 1) = P(S_{2m-1}\geq 1) + P(S_{2m-1} = 1) (2p-1)(1-p) > P(S_{2m-1} \geq 1). $$ Since $P(S_1 \geq 1) = p$, the claim follows.

$\endgroup$
3
  • $\begingroup$ How did you get rid of the 3 ? Could you expand if you want? $\endgroup$
    – Thomas
    Commented Dec 7, 2021 at 1:36
  • $\begingroup$ @Thomas I used that $P(S_{2m-1}\geq 3) + P(S_{2m-1}=1) = P(S_{2m-1}> 0)$, since $S_{2m-1}$ assumes only odd integer values. I have slightly changed notation to emphasize the fact. Hope this explains! $\endgroup$ Commented Dec 7, 2021 at 10:52
  • $\begingroup$ Perfect thank you ! $\endgroup$
    – Thomas
    Commented Dec 7, 2021 at 16:11
2
$\begingroup$

Fix $p>\frac{1}{2}$, we have to show $P\left(X>\frac{n}{2}\right)-p>0$, for all odd $n$ values, s.t., $X \sim B(n,p)$.

Proof by induction on $m \in \mathbb{Z^+}$, where $n=2m+1$ may go like this (can the induction step be completed from here?):

Basis: $m=1$ (i.e., $n=3$), $X \sim B(3,p)$, $P\left(X>\frac{n}{2}\right)-p={3 \choose 2}p^2(1-p)+p^3=3p^2+2p^3-p$. Now, let's observe that $f(p)=3p^2+2p^3$ is increasing in $p$ for $p \geq 0$, Hence, for $p>\frac{1}{2}$, we have, $f(p)>f(1/2)=1 \implies P\left(X>\frac{n}{2}\right)-p = f(p)-p>1-p\geq 0$.

Hypothesis: Let $m=r-1$, i.e., $n=2r-1$, $X \sim B(2r-1,p)$ and $P\left(X>\frac{n}{2}\right)-p = \sum\limits_{k=\lfloor n/2 \rfloor+ 1}^n \binom{n}{k} p^k (1-p)^{n-k}-p = \sum\limits_{k=r}^{2r-1} \binom{2r-1}{k} p^k (1-p)^{2r-1-k}-p>0$

Induction Step: For $m=r$, i.e., $n=2r+1$, we have $X \sim B(2r+1,p)$. Now we need to show $P\left(X>\frac{n}{2}\right)-p = \sum\limits_{k=r+1}^{2r+1} \binom{2r+1}{k} p^k (1-p)^{2r+1-k}-p>0$.

Let $g(r)= \sum\limits_{k=r}^{2r-1} \binom{2r-1}{k} p^k (1-p)^{2r-1-k}$. To prove the induction step, it suffices to show that $g(r+1)>g(r),\;\forall{r}\geq 1$, when we have $p>\frac{1}{2}$, which we can see below numerically with the following R code (it seems to be independent of $p$ as long as we have $p>\frac{1}{2}$):

n <- seq(3,201,2)
plot(n, pbinom(n/2, n, 0.51, lower.tail=FALSE), type='l')
for (p in seq(0.6,1,0.1)) {
  lines(n, pbinom(n/2, n, p, lower.tail=FALSE))
}

enter image description here

Now, $g(r+1)-g(r)=\sum\limits_{k=r+1}^{2r+1} \binom{2r+1}{k} p^k (1-p)^{2r+1-k}-\sum\limits_{k=r}^{2r-1} \binom{2r-1}{k} p^k (1-p)^{2r-1-k}$, it boils down to the inequality that $g(r+1)-g(r)>0$ (that we have to prove), the meaning of this is intuitive though, probability obtained with majority voting should increase as the number of experiments ($r$) increases.

$\endgroup$

You must log in to answer this question.

Not the answer you're looking for? Browse other questions tagged .