Student Number Semester 1 Assessment, 2020 School of Mathematics and Statistics MAST20004 Probability This exam consists of 27 pages (including this page) Authorised materials: printed one-sided copy of the Exam or the Masked Exam made available earlier (or an offline electronic PDF reader), two double-sided A4 handwritten or typed sheets of notes, and blank A4 paper. Calculators of any sort are NOT allowed. Instructions to Students • You should attempt all questions. • There is a table of normal distribution probabilities and Matlab output at the end of this question paper. • There are 9 questions with marks as shown. The total number of marks available is 120. Supplied by download for enrolled students only— c©University of Melbourne 2020 MAST20004 Probability Semester 1, 2020 Question 1 (10 marks) Consider a random experiment with sample space Ω. (a) Write down the axioms which must be satisfied by a probability mapping P defined on the set of events of the experiment. (b) Using the axioms, prove that for any events A and B where B ⊆ A, P(B) ≤ P(A). Page 2 of 27 pages MAST20004 Probability Semester 1, 2020 (c) Let A1, A2, A3, . . . be a sequence of events in Ω. Prove that P ( ∞⋃ n=1 An ) ≤ ∞∑ n=1 P(An). Page 3 of 27 pages MAST20004 Probability Semester 1, 2020 Question 2 (9 marks) A bag has three coins in it, one is fair, and the other two are weighted so the probability of a head coming up are 512 and 1 3 , respectively. You choose a coin at random from the bag and toss it. (a) What is the probability of a head showing on the coin? (b) Given a head is showing, what is the probability you tossed the fair coin? Page 4 of 27 pages MAST20004 Probability Semester 1, 2020 (c) Given a head is showing, if you toss the same coin again, what is the probability that you get a head? Do not attempt to calculate the final answer. Leave your answer in terms of products and quotients of fractions. Page 5 of 27 pages MAST20004 Probability Semester 1, 2020 Question 3 (12 marks) The Weibull cumulative distribution function FX is given by FX(x) = { 1− e−(x/β)γ , x ≥ 0 0, otherwise, where β > 0 and γ > 0 are parameters. (a) How could a realisation of a Weibull random variable be generated from an R(0, 1) random number generator? Page 6 of 27 pages MAST20004 Probability Semester 1, 2020 (b) Let Y = Xγ . Derive the cumulative distribution function of Y , identify the distribution of Y , and write down E(Y ). (c) Let Z = min(Y,M) where M is a positive finite number. Using the tail probabilities formula for the mean, derive an expression for E(Z). Page 7 of 27 pages MAST20004 Probability Semester 1, 2020 Question 4 (19 marks) Let X and Y have joint probability density function given by f(X,Y )(x, y) = { cxy, 0 < y < x < 2 0, otherwise where c is a constant. (a) Plot the region where f(X,Y )(x, y) is nonzero. Page 8 of 27 pages MAST20004 Probability Semester 1, 2020 (b) Find the constant c. (c) Find fY (y), the marginal probability density function of Y . Page 9 of 27 pages MAST20004 Probability Semester 1, 2020 (d) Find fX|Y (x|y), the conditional probability density function of X given Y = y. (e) Evaluate P ( X < 32 |Y = 1 ) . Page 10 of 27 pages MAST20004 Probability Semester 1, 2020 (f) Evaluate P ( X < 32 |Y > 1 ) . Page 11 of 27 pages MAST20004 Probability Semester 1, 2020 (g) Are X and Y independent? Justify your answer. Page 12 of 27 pages MAST20004 Probability Semester 1, 2020 Question 5 (18 marks) Toss a fair coin and let N be the number of tails observed before the first head appears. Now roll a fair die N times and let X be the number of times the number “6” is observed in the N rolls. (a) Find E(X|N) and V (X|N). (b) Evaluate E(X). (c) Evaluate V (X). Page 13 of 27 pages MAST20004 Probability Semester 1, 2020 (d) Find the conditional probability generating function PX|N (z). (e) Find the probability generating function of X and identify the distribution of X by name. Page 14 of 27 pages MAST20004 Probability Semester 1, 2020 (f) Find the conditional probability mass function of N given X = x, for x = 0, 1, 2, . . .. Page 15 of 27 pages MAST20004 Probability Semester 1, 2020 Question 6 (11 marks) The price of a stock at the beginning of the trading day is 10 dollars. The price of the same stock halfway through the trading day is S1 = 10e X , and at the end of the trading day is S2 = 10e Y , where (X,Y ) is a bivariate normal random variable with mean parameters (µX , µY ) = ( 1 2 , 1 ) , variance parameters ( σ2X , σ 2 Y ) = (4, 9), and ρ = 1√ 2 . (a) Calculate the probability that the stock has a higher price halfway through the trading day than at the beginning of the trading day. (b) If you buy one share of the stock at the start of the trading day and sell it halfway through the trading day, how much money would you expect to make (losses count as negative)? Page 16 of 27 pages MAST20004 Probability Semester 1, 2020 (c) Given the price of the stock at the end of a trading day was 10e4 dollars, what is the probability the price halfway through that day was lower than 10 dollars? Page 17 of 27 pages MAST20004 Probability Semester 1, 2020 Question 7 (20 marks) Let X d = R(0, 1). (a) For t 6= 0, derive the moment generating function of X. (b) State the value of MX(0) justifying your answer. (c) Derive the moment generating function of Y = X − 12 . Page 18 of 27 pages MAST20004 Probability Semester 1, 2020 (d) Calculate the skewness of X, that is, κ3 = E ( (X − µX)3 ) , and give an interpretation for your answer. (e) Calculate the kurtosis of X, that is, κ4 = E ( (X − µX)4 ) − 3σ4. Is the kurtosis of X positive, negative, or zero? Justify your answer and give an inter- pretation for it. Page 19 of 27 pages MAST20004 Probability Semester 1, 2020 (f) Let X1, X2, . . . be a sequence of independent random variables where each one has the same distribution as X d = R(0, 1). Derive the moment generating function of Yn = X1 +X2 + . . .+Xn − n 2√ n . Page 20 of 27 pages MAST20004 Probability Semester 1, 2020 (g) Use the moment generating function of Yn to prove that Yn converges to N ( 0, 112 ) in distribution as n→∞. Hint: you may wish to use ex ≈ 1 + x+ x22 + x 3 6 for small x. Page 21 of 27 pages MAST20004 Probability Semester 1, 2020 Question 8 (10 marks) Let X d = exp(3) and W d = N(−6, 25). (a) Explain how a realisation of U d = R(0, 1) can be used to generate a realisation of X. (b) Explain how a realisation of Z d = N(0, 1) can be used to generate a realisation of W . (c) Explain how to calculate an estimate of E(XW ) from 1,000 realisations of the random variable U d = R(0, 1) and 1,000 realisations of the random variable Z d = N(0, 1). Note that the “rand” command in Matlab generates a realisation of U and the “randn” command generates a realisation of Z. Page 22 of 27 pages MAST20004 Probability Semester 1, 2020 (d) Let Y = ∫ X 0 3e−3tdt. What is the distribution of Y ? Justify your answer. Page 23 of 27 pages MAST20004 Probability Semester 1, 2020 Question 9 (11 marks) The weather in Melbourne on any day can be in one of three states: 1=“wet”, 2=“cold”, or 3=“miserable”. The state of the weather can be described by a Markov chain model with transition probability matrix P = 3 10 1 4 9 20 2 5 1 10 1 2 1 4 2 5 7 20 . (a) Which underlying assumption has been made so that this situation can be modelled as a Markov chain? (b) For this part justify your answers where necessary, and you may wish to use the Matlab output at the end of this question paper to reduce your calculations. Suppose on Monday, the weather is cold. What is the probability that the weather will be (i) miserable on Wednesday of the same week? (ii) wet on Thursday of the same week? Page 24 of 27 pages MAST20004 Probability Semester 1, 2020 (iii) cold on all days from Tuesday to Thursday of the same week? (c) Explain two methods that can be used for finding the stationary distribution of the Markov chain, one of which uses the Matlab output at the end of this question paper. Give the stationary distribution of the Markov chain and interpret your answer. End of Exam—Total Available Marks = 120 Page 25 of 27 pages MAST20004 Probability Semester 1, 2020 Page 26 of 27 pages MAST20004 Probability Semester 1, 2020 Page 27 of 27 pages
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