Recent content by wid308

its the probability density function for a continuous distribution the integral gives the total area under the pdf

ok thanks. nope...no idea for the second part

E(X) = [-∞]\int[/∞] g(x).f(x) dx let g(x) = X E(X) = [-∞]\int[/∞] 1.f(x) dx = 1. [-∞]\int[/∞] f(x) dx = 1 P.S: [-∞]\int[/∞] is the integral of -infinity to infinity

expectation is the expected value or mean. I have tried the first one using probability density function. but am not sure of my answer. while the others I have no idea how to attempt them thank you

hello! can any1 please help me with the following proofs? thanks let X and Y be random variables. prove the following: (a) if X = 1, then E(X) = 1 (b) If X ≥ 0, then E(X) ≥ 0 (c) If Y ≤ X, then E(Y) ≤ E(X) (d) |E(X)|≤ E(|X|) (e) E(X)= \sumP(X≥n)