2) The joint probability density function of random variables X and Y is fx,(x,y) ={ fxy 0
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- The correlation between X and Y Select one or more: a. is the covariance squared b. cannot be negative since variances are always positive. c. is given by corr(X, Y) = cov(X,Y)/var(X)var(Y)cov(X,Y)/var(X)var(Y) d. can be calculated by dividing the covariance between X and Y by the product of the two standard deviationsThe table gives the joint probability distribution of the number of sports an individual plays (X) and the number of times she may get injured while playing (Y) X=1 X=2 X=3 0.12 0.08 0.15 0.06 0.05 0.05 0.10 0.03 0.15 0.15 0.04 0.02 Y=4 Y=3 Y=2 Y=1 The covariance between X and Y, oxy, is (Round your answer to two decimal places Enter a minus sign if your answer is negative) The correlation between X and Y, corr(X, Y), is (Round your answer to two decimal places Enter a minus sign if your answer is negative.) An increase in the number of sports an individual plays will tend to * the number of times she may got injured while playingA) Caused by a third variable B) uncorrelated ) negative effect 0.fb/ orrrte D) direct cause-and-effect 7) The formula for the correlation coefficient r= n (Σxy)-(Σx) (Σν) means 7) n(Ex2)- (Ex)2n(2y2)- (2y) D A) r is the ratio of the covariance to the product of the standard deviation of XY B) r is the ratio of the covariation to the square root of the product of the variation in X and the variation in Y. C)ris the ratio of the covariance to the square root of the product of the variation in X and the variation in Y. D) r is the ratio of the covariation to the product of the standard deviations of X and Y.
- Determine the covariance and correlation for the following joint probabilitydistribution:x 1 1 2 4y 3 4 5 6fXY(x,y) 1/8 1/4 1/2 1/Fill out the table giving the joint and marginal PMFs for X and Y. Find E[X] and E[Y]. Find the covariance of X and Y. Are X and Y independent?Let X and Y be jointly continuous random variables with joint PDF cx +1, 2,y> 0, x+ y<1 0, fx,x (x, y) = otherwise. Then the constant c= And the probability that P(Y < 2X²) = ;: Here a = and b =
- Suppose that Y is a continuous random variable. Show EY yfr(y)dy.Let X1, X2,... , Xn be independent Exp(A) random variables. Let Y = X(1)min{X1, X2, ... , Xn}. Show that Y follows Exp(nA) dis- tribution. Hint: Find the pdf of YExercise 3. Let X be a random variable with mean u and variance o2. For a E R, consider the expectation E((X – a)²). a) Write E((X – a)²) in terms of a, µ and o2. b) For which value a is E((X – a)²) minimal? c) For the value a from part (b), what is E((X – a)²)?
- A random process is defined as X (t) = A.cos cot, where 'o' is a constant and A' is a uniform random variable over (0,1 ). Find the auto correlation and auto covariance of X (t).Let X and Y be random variables with Var(X)=0.64, Var(Y)=0.81, and Cov(X,Y) = 0.5. Find each of the following to two decimal places (if applicable). (a) Coefficient of correlation p(X,Y) 0.694 (b) Var(3X+Y+1) 9.57 (c) Cov(-2Y, 3X+Y+1) (d) p(-2Y, 3X+Y+1)Let X and Y be independent random variables with means x,y and variances o, oy. Find an expression for the correlation of XY and Y in terms of these means and variances.