EBK AN INTRODUCTION TO MATHEMATICAL STA
6th Edition
ISBN: 9780134114248
Author: Marx
Publisher: YUZU
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Chapter 5.7, Problem 6Q
l match
To determine
To prove:
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Chapter 5 Solutions
EBK AN INTRODUCTION TO MATHEMATICAL STA
Ch. 5.2 - A random sample of size...Ch. 5.2 - The number of red chips and white chips in an urn...Ch. 5.2 - Use the sample y1=8.2,y2=9.1,y3=10.6, and y4=4.9...Ch. 5.2 - Suppose a random sample of size n is drawn from...Ch. 5.2 - Given that y1=2.3,y2=1.9, and y3=4.6 is a random...Ch. 5.2 - Use the method of maximum likelihood to estimate ...Ch. 5.2 - An engineer is creating a project scheduling...Ch. 5.2 - The following data show the number of occupants in...Ch. 5.2 - For the Major League Baseball seasons from 1950...Ch. 5.2 - (a) Based on the random sample...
Ch. 5.2 - Find the maximum likelihood estimate for in the...Ch. 5.2 - A random sample of size n is taken from the pdf...Ch. 5.2 - If the random variable Y denotes an individuals...Ch. 5.2 - For the negative binomial pdf...Ch. 5.2 - The exponential pdf is a measure of lifetimes of...Ch. 5.2 - Suppose a random sample of size n is drawn from a...Ch. 5.2 - Let y1,y2,...,yn be a random sample of size n from...Ch. 5.2 - Prob. 18QCh. 5.2 - A criminologist is searching through FBI files to...Ch. 5.2 - Prob. 20QCh. 5.2 - Suppose that Y1=8.3,Y2=4.9,Y3=2.6, and Y4=6.5 is a...Ch. 5.2 - Find a formula for the method of moments estimate...Ch. 5.2 - Calculate the method of moments estimate for the...Ch. 5.2 - Find the method of moments estimates for and 2,...Ch. 5.2 - Use the method of moments to derive estimates for...Ch. 5.2 - Bird songs can be characterized by the number of...Ch. 5.2 - Prob. 27QCh. 5.3 - A commonly used IQ test is scaled to have a mean...Ch. 5.3 - The production of a nationally marketed detergent...Ch. 5.3 - Mercury pollution is widely recognized as a...Ch. 5.3 - A physician who has a group of thirty-eight female...Ch. 5.3 - Suppose a sample of size n is to be drawn from a...Ch. 5.3 - What confidence would be associated with each of...Ch. 5.3 - Five independent samples, each of size n, are to...Ch. 5.3 - Suppose that y1,y2,...,yn is a random sample of...Ch. 5.3 - If the standard deviation () associated with the...Ch. 5.3 - In 1927, the year he hit sixty home runs, Babe...Ch. 5.3 - A thirty-second commercial break during the...Ch. 5.3 - During one of the first beer wars in the early...Ch. 5.3 - The Pew Research Center did a survey of 2253...Ch. 5.3 - If (0.57,0.63) is a 50% confidence interval for p,...Ch. 5.3 - Suppose a coin is to be tossed n times for the...Ch. 5.3 - On the morning of November 9, 1994the day after...Ch. 5.3 - Which of the following two intervals has the...Ch. 5.3 - Prob. 18QCh. 5.3 - Prob. 19QCh. 5.3 - Prob. 20QCh. 5.3 - Prob. 21QCh. 5.3 - A public health official is planning for the...Ch. 5.3 - Prob. 23QCh. 5.3 - Given that a political poll shows that 52% of the...Ch. 5.3 - Prob. 25QCh. 5.3 - Suppose that p is to be estimated by Xn and we are...Ch. 5.3 - Let p denote the true proportion of college...Ch. 5.3 - Prob. 28QCh. 5.4 - Two chips are drawn without replacement from an...Ch. 5.4 - Suppose a random sample of size n=6 is drawn from...Ch. 5.4 - Prob. 3QCh. 5.4 - A sample of size n=16 is drawn from a normal...Ch. 5.4 - Suppose X1,X2,...,Xn is a random sample of size n...Ch. 5.4 - Prob. 6QCh. 5.4 - Let Y be the random variable described in Example...Ch. 5.4 - Suppose that 14, 10, 18, and 21 constitute a...Ch. 5.4 - A random sample of size 2, Y1 and Y2, is drawn...Ch. 5.4 - A sample of size 1 is drawn from the uniform pdf...Ch. 5.4 - Suppose that W is an unbiased estimator for . Can...Ch. 5.4 - We showed in Example 5.4.4 that 2=1ni=1n(YiY)2 is...Ch. 5.4 - As an alternative to imposing unbiasedness, an...Ch. 5.4 - Let Y1,Y2,...,Yn be a random sample of size n from...Ch. 5.4 - An estimator n=h(W1,...,Wn) is said to be...Ch. 5.4 - Is the maximum likelihood estimator for 2 in a...Ch. 5.4 - Let X1,X2,...,Xn denote the outcomes of a series...Ch. 5.4 - Suppose that n=5 observations are taken from the...Ch. 5.4 - Let Y1,Y2,...,Yn be a random sample of size n from...Ch. 5.4 - Given a random sample of size n from a Poisson...Ch. 5.4 - If Y1,Y2,...,Yn are random observations from a...Ch. 5.4 - Suppose that W1 is a random variable with mean ...Ch. 5.5 - Let Y1,Y2,...,Yn be a random sample from...Ch. 5.5 - Let X1,X2,...,Xn be a random sample of size n from...Ch. 5.5 - Suppose a random sample of size n is taken from a...Ch. 5.5 - Let Y1,Y2,...,Yn be a random sample from the...Ch. 5.5 - Prob. 5QCh. 5.5 - Let Y1,Y2,...,Yn be a random sample of size n from...Ch. 5.5 - Prove the equivalence of the two forms given for...Ch. 5.6 - Let X1,X2,...,Xn be a random sample of size n from...Ch. 5.6 - Let X1,X2, and X3 be a set of three independent...Ch. 5.6 - If is sufficient for , show that any one-to-one...Ch. 5.6 - Show that 2=i=1nYi2 is sufficient for 2 if...Ch. 5.6 - Let Y1,Y2,...,Yn be a random sample of size n from...Ch. 5.6 - Let Y1,Y2,...,Yn be a random sample of size n from...Ch. 5.6 - Suppose a random sample of size n is drawn from...Ch. 5.6 - Suppose a random sample of size n is drawn from...Ch. 5.6 - Prob. 9QCh. 5.6 - Prob. 10QCh. 5.6 - Prob. 11QCh. 5.7 - How large a sample must be taken from a normal pdf...Ch. 5.7 - Let Y1,Y2,...,Yn be a random sample of size n from...Ch. 5.7 - Suppose Y1,Y2,...,Yn is a random sample from the...Ch. 5.7 - An estimator n is said to be squared-error...Ch. 5.7 - Suppose n=Ymax is to be used as an estimator for...Ch. 5.7 - Prob. 6QCh. 5.8 - Prob. 1QCh. 5.8 - Find the squared-error loss [L(,)=()2] Bayes...Ch. 5.8 - Prob. 3QCh. 5.8 - Prob. 4QCh. 5.8 - Prob. 5QCh. 5.8 - Suppose that Y is a gamma random variable with...Ch. 5.8 - Prob. 7QCh. 5.8 - Find the squared-error loss Bayes estimate for in...Ch. 5.8 - Prob. 9Q
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- Suppose that X is a continuous unknown all of whose values are between -3 and 3 and whose PDF, denoted f , is given by f ( x ) = c ( 9 − x^2 ) , − 3 ≤ x ≤ 3 , and where c is a positive normalizing constant. What is the variance of X?arrow_forwardConsider a real random variable X with zero mean and variance σ2X . Suppose that wecannot directly observe X, but instead we can observe Yt := X + Wt, t ∈ [0, T ], where T > 0 and{Wt : t ∈ R} is a WSS process with zero mean and correlation function RW , uncorrelated with X.Further suppose that we use the following linear estimator to estimate X based on {Yt : t ∈ [0, T ]}:ˆXT =Z T0h(T − θ)Yθ dθ,i.e., we pass the process {Yt} through a causal LTI filter with impulse response h and sample theoutput at time T . We wish to design h to minimize the mean-squared error of the estimate.a. Use the orthogonality principle to write down a necessary and sufficient condition for theoptimal h. (The condition involves h, T , X, {Yt : t ∈ [0, T ]}, ˆXT , etc.)b. Use part a to derive a condition involving the optimal h that has the following form: for allτ ∈ [0, T ],a =Z T0h(θ)(b + c(τ − θ)) dθ,where a and b are constants and c is some function. (You must find a, b, and c in terms ofthe information…arrow_forwardWhat is the Marginal PDF of f(x)=2? Is the event independent?arrow_forward
- Suppose that X is a continuous unknown all of whose values are between -5 and 5 and whose PDF, denoted f, is given by f ( x ) = c ( 25 − x^2 ) , − 5 ≤ x ≤ 5 , and where c is a positive normalizing constant. What is the expected value of X^2?arrow_forwardDerive a general expression for the variance of net future loss Var(L) with a constant force of interest δ under each of the following models:i. μ_x(t) = μii. μ_x(t) = 1/(ω-x)arrow_forwardSuppose X1, ..., Xn have been randomly sampled from a normal distribution with mean 0 and unknown variance sigma^2, and let U = c * i=1 -> n summation (X_ i)^2 , where c is a constant. Find the value of c that minimises the Mean Squared Error (MSE)arrow_forward
- Suppose that n observations are chosen at random from a continuous pdf fY(y). What is the probability that the last observation recorded will be the smallest number in the sample?arrow_forwardSuppose that a study of a certain computer system reveals that the response time, in seconds, has an exponential distribution with density curve f(x) = (1/3)e(-x/3) for x > 0 and f(x) = 0 otherwise. What is the probability that response time exceeds 5 seconds? What is the probability that response time exceeds 10 seconds?arrow_forwarda. What is the probability that the lifetime X of the first component exceeds 3? b. What are the marginal pdf's of X and Y? Are the two lifetimes independent? x. What is the probability that the lifetime of at least one component exceeds 3?arrow_forward
- Consider a random variable X with E[X] = 10, and X being positive. Estimate E[ln√X] using Jensen’s inequality.arrow_forwardSuppose X is a continuous random variable with a triangular distribution defined over 0 to 2. Picture two right triangles pushed together with a peak at 1. f(x) = 0 for x < 0 f(x) = x for 0 < x < 1f(x) = 2 - x for 1 < x < 2f(x) = 0 for x > 2a. Calculate E(X).b. Calculate Var(X)c. Let G(X)=8+3X. What is the E[G(X)] and the variance of G(X)?arrow_forward
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