Given a distribution p(x), there are two things that can be calculated.
- Value of x for which p(x) is maximum.
- Most probable value of x weighted over p(x).
Would these two values of x be the same?
Given a distribution p(x), there are two things that can be calculated.
Would these two values of x be the same?
No.
To make it easier for comprehension, we may consider the discrete case, where 'p(x) is maximum' refers to the event that takes place most, while 'Most probable value of x weighted over p(x).' (expectation) refers to the average value. In a extreme case if you have a dice with four '0's and two '1's, the value of x for which p(x) is maximum is clearly $0$ and the most probable value of x weighted over p(x) is $1/3$, which is even not a value you would ever see in any cases.
Also, it's actually a bit confusing when you say "Most probable value of x weighted over p(x)", for the term "Most probable value" itself means value of x for which p(x) is maximum. I guess you are trying to refer to the expectation.
My answer might not be a full-fledge solution but I think it should still help.
Clearly, the most probable value of x weighted over $P(x)$ is an expected value $E[X]$. Now, assume that what you claim is true. Let's say that there is a discrete probability where $P(x=12)=0.2$ and $P(x=2)=0.8$ Clearly, the value of $x$ for which $P(x)$ is maximum is $2$ but the expected value is $E[X]=\sum^2_{i=1}P(X=x_i)x_i=P(x=2)*2+P(x=12)*12=0.8*2+0.2*12=4.0$. Well, $12\ne4$ and I would argue that even though $4.0$ is closer to $2$ than $12$, you can't just say that these values are the same
The expected value and most probable value can but need not coincide. Consider a random variable $X$ defined by $P(X=0)=0.9$ and $P(X=1)=0.1$. The most probable value is $0$, yet the expected value is $0.1$.
If your idea of “most probable value weighted over the distribution” is the expected value, then, no, these values need not be equal.