Test P Flashcards
Cov(X,X) = ?
Var(X)
What equation relates Var(X,Y) with covariance?
Var(X,Y) = Var(X) + Var(Y) + 2Cov(X,Y)
Shortcut formula for Var(X)?
Var(X) = E(X2) - E(X)2
Var(aX) = ?
a2Var(X)
Cov(aX1 + bX2, Y1 + Y2) = ?
aCov(X1,Y1) + aCov(X1,Y2) + bCov(X2,Y1) + bCov(X2,Y2)
If X and Y are independent, then MX+Y(t) = ?
MX(t) x MY(t)
If X and Y are independent, then Var(X+Y) = ?
Var(X) + Var(Y)
fY|X=x(y|X=x) = ?
fXY(x,y)/fX(x)
plug in x
correlation coefficient p?
p(x,y) = Cov(X,Y)/[√Var(X)√Var(Y)]
Cov(X,Y) = ?
E(XY) - E(X)E(Y)
Given random variables Y1 , … , Yn with common CDF FY(y),
let X = max(Y1 , … , Yn).
What would FX(x) equal?
(FY(x))n
relationship between f(y) and F(y)?
f(y) = F’(y)
E(X) = ?
X is continuous with PDF fX(x)
E(X) = ∫x fx(x) dx
Bayes Theorem:
Pr(U|D) = ?
where S,P,U are a partition of probability space
Pr(D|U)Pr(U)
____________________________
Pr(D|S)Pr(S) + Pr(D|P)Pr(P) + Pr(D|U)P(U)
Necessary condition for independence of two continuous random variables:
region where joint density is positive is _________, and if joint density is product of _______.
What can you conclude about Cov(X,Y) if X and Y meet these conditions?
rectangular with sides parallel to axe
function of first variable only and function of second variable only
Cov(X,Y) = 0
Variance of uniform distribution from (a,b)?
(b-a)2/12
Darth Vader Rule
E(max(T,2)) = ?
2 + ∫2∞ sT(x) dx
Survival function of exponential random variable T with mean 3?
sT(t) = e-t/3
Survival function in terms of F?
s(x) = 1 - F(x)
Darth Vader Rule
E(X) = ? in terms of s(x)
E(X) = ∫0∞s(x) dx
Let’s say F(x) = 0 for 0 < x < 1
and F(x) = (1-(1/y3))3 for x > 1
Describe s(x)
s(x) = 1 for 0 < x < 1
s(x) = 1 - (1/y3))3
If events A and B are independent, what 3 things are true:
Pr(A∩B) = Pr(A)Pr(B)
Pr(A|B) = Pr(A)
Pr(B|A) = Pr(B)
if X = g(Y) and fx is PDF of X
then fY(y) = ?
fX(x(y)) |dx/dy|
∫0∞ yme-my dy = ?
Mean of exponential random variable with hazard rate m;
1/m