I have come up with the following understanding about Expectation of RV.
Please, correct me if I am wrong.
Definition: Expected value of a RV says that, if a random experiment is repeated n number of times, what would be the value that you expect to see most of the times. Expected value of a Random Variable is a value. It is not a probability.
Example: In case of a dice, if the dice is rolled $n$ number of times, the value we would see most of the times is 3.5.
Calculation: We don't have to repeat the same experiment $n$ number of times to find the expected value of a random variable. It can be done using the random variable and its associated probability distribution. In case of a dice,
$ \sum_{x=1}^6 x(1/6) = 1*(1/6) + 2*(1/6) + 3*(1/6) + 4*(1/6) + 5*(1/6) + 6*(1/6) = 3.5 $
Continuous Case
If $X$ is a continuous random variable with density function $f_X(x),$ then the expectation of $X$ is $\displaystyle E(X)=\int_{-\infty}^\infty x\,f_X(x)\,dx$
If $Y=g(X)$ is a function of $X$(i.e. a density function)$,$ then $\displaystyle E(Y)=\int_{-\infty}^\infty g(x)\,f_X(x)\,dx$
Edit:
After reading comments and answers,
Definition:
Expected value of a RV says that, if a random experiment is repeated n number of times, what would be the average value of the outcomes.
Expected value of a Random Variable is a value. It is not a probability.
Example:
In case of a dice, if the dice is rolled $n$ number of times, the average value of the outcomes would be 3.5.