i) State, with parameter(s), the probability distribution of the statistic, T = Σ=Wi?
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- X and Y are continuous random variables with pdf f(x,y) = 2x for0 ≤x ≤y ≤1, and f(x,y) = 0 otherwise. Find the conditional expectation ofY given X = x.Two archers will simultaneously shoot once at a target. Let Xi , i = 1, 2, be marksman i's horizontal error, measured in meters. If the target's position is (a, b), and marksman i's shot ends up at (x, y), then Xi = (x - a). These errors are modeled by X1 ~ N(0, 0.5) and X2 ~ N(0, 1). What is the probability that both shots will be within 1 meter of the target, in the horizontal direction?When studying the spread of an epidemic, we assume that the probability that an infected individual will spread the disease to an uninfected individual is a function of the distance between them. Consider a circular city of radius 10 miles in which the population is uniformly distributed. For an uninfected individual at a fixed point A(x0, y0), assume that the probability function is given by f(P)=1/20[20-d(P,A)] where d(P,A) denotes the distance between points P and A. Evaluate the integral for the case in which A is the center of the city and for the case in which A is located on the edge of the city. Where would you prefer to live?
- i)only Let (X1,...,Xn), n ≥ 2, be a random sample from a distribution with discrete probability density fθ,j,whereθ ∈ (0,1), j = 1, 2, fθ,1 is the Poisson distribution with mean θ,andfθ,2 is the binomial distribution with size 1 and probability θ. (i) Show that T = ni=1Xi is not sufficient for (θ,j).Let X~N(0,1). Let Y=2X. Find the distribution of Y using the moment generating function technique.Let (X, Y ) be independent and uniformly distributed random variables (RVs) on the interval[0, 1]. Equivalently, let (X, Y ) be a point chosen uniformly at random in the unit box [0, 1] × [0, 1] on the(x, y) plane. Define the RV Z ≜ √X^2−Y^2 as the random distance of the point (X, Y ) from the origin (0, 0). Find the cumulative distribution function (CDF) for the RV Z.
- Two sharpshooters will simultaneously shoot once at a target. Let Xi , i = 1, 2, be marksman i's horizontal error, measured in meters. If the target's position is (a, b), and marksman i's shot ends up at (x, y), then Xi = (x - a). These errors are modeled by X1 ~ N(0, 0.5) and X2 ~ N(0, 1). What is the probability that both shots will be within 1 meter of the target, in the horizontal direction?Suppose that the random variables X, Y, Z have multivariate PDFfXYZ(x, y, z) = (x + y)e−z for 0 < x < 1, 0 < y < 1, and z > 0. Find (a) fXY(x, y), (b) fYZ(y, z), (c) fZ(z)Let (X1,...,Xn), n ≥ 2, be a random sample from a distribution with discrete probability density fθ,j,whereθ ∈ (0,1), j = 1, 2, fθ,1 is the Poisson distribution with mean θ,andfθ,2 is the binomial distribution with size 1 and probability θ. (i) Show that T = ni=1Xi is not sufficient for (θ,j).
- Let Y be a continuous random variable. Let c be a constant. PROVE Var (Y) = E (Y2) - E (Y)2Let X and Y be continuous random variables with joint distribution function, F (x,y). Let g (X,Y) and h (X,Y) be functions of X and Y. PROVE Cov (X,Y) = E[XY] - E[X] E[Y]b) Let Y1, Y2, ..., Yn be a random sample from a population with probability density function in part a). Show that the best test for the hypothesis in part a) rejects Ho if |yi <c i=1 where c solves the probability equation a = P(II1Yis c[0 = 2). c) Let X1,X2, ..., Xn be a random sample from GAMMA(2,ß) distribution, and consider Y = E-,Xi- Show whether or not Y is a pivotal quantity and give its distribution.
