Answer:
integers
Step-by-step explanation:
hope this is helpful
Answer:
Below are the responses to the given question:
Step-by-step explanation:
Let X become the random marble variable & g have been any function.
Now.
For point a:
When X is discreet, the g(X) expectation is defined as follows
Then there will be a change of position.
E[g(X)] = X x∈X g(x)f(x)
If f is X and X's mass likelihood function support X.
For point b:
When X is continuing the g(X) expectations is calculated as, E[g(X)] = Z ∞ −∞ g(x)f(x) dx, where f is the X transportation distances of probability.If E(X) = −∞ or E(X) = ∞ (i.e., E(|X|) = ∞), they say it has nothing to expect from EX is occasionally written to stress that a specific probability distribution X is expected.Its expectation is given in the form of,E[g(X)] = Z x −∞ g(x) dF(x). , sometimes for the continuous random vary (x). Here F(x) is X's distributed feature. The anticipation operator bears the lineage of comprehensive & integral features. The superposition principle shows in detail how expectation maintains equality and is a skill.
I think it’s 5 because if u do 1.5 / 3in it’s turn out to be 0.5
1) false
2) t is the independant variable, C is the dependant variable
3) true
Answer:
you cannot have a greatest common factor when you are adding, only when multiplying or dividing.
Step-by-step explanation:
