Variables - Probablity - Exam, Exams of Probability and Statistics

This is the Exam of Probablity which includes Watched Gymnastics, Gymnastics and Baseball, Baseball and Soccer, Gymnastics And Soccer, Percentage, Primary Care Physician, Referral to a Specialist, Probability, Results etc. Key important points are: Variables, Densities, Joint Density, Uniform, Marginal Densitie, Independent, Conditional Densities, Independent Exponentials, Mass Functions, Random Variables

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2012/2013

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Math 411 - Fall 2012 - Practice for the final Exam.
1. Pick a point Xuniformly on [0,1] and then pick a point Yuniformly on [0, X].
a. Compute the densities fXand fY|X(y|x).
b. Find the joint density of (X, Y ).
c. Compute the densities fYand fX|Y(x|y).
d. Is it true that Xis uniform on [Y, 1]? Justify your answer.
2. Let Xand Ybe continuous random variables with joint density function
()f(x, y) = cey,0< x < y < .
a. Find c.
b. Compute the marginal densities.
c. Is it true that X, Y are independent?
d. Compute the conditional densities fX|Y(x|y), fY|X(y|x).
e. Compute the probability P(0 X1|Y= 1).
f. Let Z1, Z2two independent exponentials with parameter 1 each. Let X=Z1
and Y=Z1+Z2. Show that (X, Y ) have joint density as in ().
3. The joint probability mass function of the random variables X, Y is
p(0,1) = p(0,0) = p(0,1) = p(1,0) = 1
4, p(1,1) = p(1,1) = 0.
a. Compute the marginal probability mass functions of Xand Y.
b. Is it true that Xand Yare independent?
c. Compute EXY , EX, EY.
d. Compte the Cov(X, Y ).
4. Let X, Y, Z be independent and uniformly distributed on (0,1).
a. Compute the probability P(XY+Z
2).
b. Compute the expectation of the random variable Z=eXY2Z.
5. Let X1, X2be independent standard normal variables. Let Y1=1
2(X1+X2),
Y2=1
2(X1X2).
a. Find the joint density of Y1, Y2.
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Math 411 - Fall 2012 - Practice for the final Exam.

  1. Pick a point X uniformly on [0, 1] and then pick a point Y uniformly on [0, X]. a. Compute the densities fX and fY |X (y|x). b. Find the joint density of (X, Y ). c. Compute the densities fY and fX|Y (x|y). d. Is it true that X is uniform on [Y, 1]? Justify your answer.
  2. Let X and Y be continuous random variables with joint density function (∗) f (x, y) = ce−y, 0 < x < y < ∞. a. Find c. b. Compute the marginal densities. c. Is it true that X, Y are independent? d. Compute the conditional densities fX|Y (x|y), fY |X (y|x). e. Compute the probability P(0 ≤ X ≤ 1 |Y = 1). f. Let Z 1 , Z 2 two independent exponentials with parameter 1 each. Let X = Z 1 and Y = Z 1 + Z 2. Show that (X, Y ) have joint density as in (∗).
  3. The joint probability mass function of the random variables X, Y is

p(0, −1) = p(0, 0) = p(0, 1) = p(1, 0) =^14 , p(1, −1) = p(1, 1) = 0.

a. Compute the marginal probability mass functions of X and Y. b. Is it true that X and Y are independent? c. Compute EXY, EX, EY. d. Compte the Cov(X, Y ).

  1. Let X, Y, Z be independent and uniformly distributed on (0, 1). a. Compute the probability P(X ≤ Y^ + 2 Z). b. Compute the expectation of the random variable Z = eX^ Y 2 Z.
  2. Let X 1 , X 2 be independent standard normal variables. Let Y 1 = √^12 (X 1 + X 2 ), Y 2 = √^12 (X 1 − X 2 ). a. Find the joint density of Y 1 , Y 2.

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b. Compute Cov(X 1 , X 2 ) and Cov(Y 1 , Y 2 ). c. Let W 1 := X 1 + X 2 , W 2 = X 2. Compute the joint density of W 1 , W 2 and Cov(W 1 , W 2 ).

  1. Assume that each year the stock market either increases by 40% or decreases by 20% with probability 12 each. Assume that you start with M dollars and let Mn be your capital after n years. Use the Law of Large Numbers to show that after n years (n is “large”) Mn will be approximately M 0 (1. 4 × 0 .8)n^2. Hint: Work with the random variable Wn := log M Mn.
  2. Let X be a non-negative random variable with expectation 1. a. Estimate the probability P(X ≥ 4) from above. b. Assume that the variance of X is 1. Use this information to estimate again the above probability. c. Assume that EX^3 = 3. Use this information to estimate again the probability in [a.]. d. Assume that X is exponential with parameter 1. Compute the probability in [a.] and compare your answer with the estimates in [a.], [b.].
  3. Let X 1 , · · · , X 10 be independent Poisson random variables with expectation 1. a. Compute the probability P(X 1 + · · · + X 10 ≥ 20). b. Use the Central Limit Theorem to give an approximation of the above proba- bility.

The final exam will be based on chapters 6 (§6.1, §6.2, §6.3.1, §6.4.4, §6.3.4, §6.4, §6.5, §6.7), Chapter 7 (§7.1, §7.2, §7.4) and Chapter 8 (§8.2, §8.3). Remember to bring a “bluebook” with you on the exam. Calculators are not allowed. Final exam: Section 501: December 12, Wed, 1–3 p.m., Section 502: December 11, Tue, 1–3 p.m. Additional office hours: Monday, Dec 3, 11:30-12:30., Thu, Dec 6, 11:00-12:00, Mon Dec 10, 11:00-12:00.