An Introduction to Mathematical Statistics and Its Applications (6th Edition)
6th Edition
ISBN: 9780134114217
Author: Richard J. Larsen, Morris L. Marx
Publisher: PEARSON
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Chapter 11.5, Problem 1Q
Suppose that
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If the PDF of X is f(x)=2x/k2 for 0<x<k, for what value of k is the variance of X equal to 2?
1. Consider the Gaussian distribution N (m, σ2).(a) Show that the pdf integrates to 1.(b) Show that the mean is m and the variance is σ.
Suppose X1, . . . , Xn are i.i.d. from a continuous distribution with p.d.f.
fθ(x) = 1/θ if 0 ≤ x ≤ θ,
where θ > 0 is an unknown parameter.
(a) Find E(X1)
(b) Find the MME for θ.
(c) Compute the variance of your MME from part (a).
Chapter 11 Solutions
An Introduction to Mathematical Statistics and Its Applications (6th Edition)
Ch. 11.2 - Crickets make their chirping sound by sliding one...Ch. 11.2 - The aging of whisky in charred oak barrels brings...Ch. 11.2 - Prob. 3QCh. 11.2 - Prob. 4QCh. 11.2 - Prob. 5QCh. 11.2 - Prob. 6QCh. 11.2 - The relationship between school funding and...Ch. 11.2 - (a) Find the equation of the least squares...Ch. 11.2 - Prob. 9QCh. 11.2 - Prob. 10Q
Ch. 11.2 - Prob. 11QCh. 11.2 - Verify that the coefficients a and b of the least...Ch. 11.2 - Prob. 13QCh. 11.2 - Prob. 14QCh. 11.2 - Prob. 15QCh. 11.2 - Prob. 16QCh. 11.2 - Prob. 17QCh. 11.2 - A graph of the luxury suite data in Question 8.2.5...Ch. 11.2 - Set up (but do not solve) the equations necessary...Ch. 11.2 - Prob. 20QCh. 11.2 - The growth of federal expenditures is one of the...Ch. 11.2 - Prob. 22QCh. 11.2 - Prob. 24QCh. 11.2 - Prob. 25QCh. 11.2 - Among mammals, the relationship between the age at...Ch. 11.2 - Prob. 27QCh. 11.2 - Years of experience buying and selling commercial...Ch. 11.2 - Prob. 29QCh. 11.2 - The following table shows a portion of the results...Ch. 11.3 - Insect flight ability can be measured in a...Ch. 11.3 - The best straight line through the Massachusetts...Ch. 11.3 - Based on the data in Question 11.2.1, the...Ch. 11.3 - Suppose an experimenter intends to do a regression...Ch. 11.3 - Prob. 5QCh. 11.3 - Prob. 6QCh. 11.3 - Prob. 7QCh. 11.3 - Set up and carry out an appropriate hypothesis...Ch. 11.3 - Test H0:1=0 versus H1:10 for the plumage...Ch. 11.3 - Prob. 10QCh. 11.3 - Derive a formula for a 95% confidence interval for...Ch. 11.3 - Which, if any, of the assumptions of the simple...Ch. 11.3 - Prob. 13QCh. 11.3 - Construct a 90% confidence interval for 2 in the...Ch. 11.3 - Regression techniques can be very useful in...Ch. 11.3 - Construct a 95% confidence interval for E(Y2.750)...Ch. 11.3 - Prob. 18QCh. 11.3 - The fuel economy (in miles per gallon) of an...Ch. 11.3 - In the radioactive exposure example in Question...Ch. 11.3 - Attorneys representing a group of male buyers...Ch. 11.3 - Prob. 23QCh. 11.3 - Show that i=1n(YiY)2=i=1n(YiYi)2+i=1n(YiY)2 for...Ch. 11.4 - Prob. 1QCh. 11.4 - Prob. 2QCh. 11.4 - Prob. 3QCh. 11.4 - Prob. 4QCh. 11.4 - Prob. 5QCh. 11.4 - Let the random variable X take on the values...Ch. 11.4 - Prob. 7QCh. 11.4 - Prob. 8QCh. 11.4 - Prob. 9QCh. 11.4 - Prob. 10QCh. 11.4 - Some baseball fans believe that the number of home...Ch. 11.4 - Many people believe that a salary bonus is a...Ch. 11.4 - The extent to which stress is a contributing...Ch. 11.4 - Burglary and larceny both involve the illegal...Ch. 11.4 - A common saying in golf is You drive for show, but...Ch. 11.5 - Suppose that X and Y have a bivariate normal pdf...Ch. 11.5 - Suppose that X and Y have a bivariate normal...Ch. 11.5 - Prob. 3QCh. 11.5 - Suppose that the random variables X and Y have a...Ch. 11.5 - Prob. 5QCh. 11.5 - Give conditions on a0,b0, and u so that...Ch. 11.5 - Prob. 7QCh. 11.5 - In a study of heart disease (79), the weight (in...Ch. 11.5 - Prob. 9QCh. 11.5 - Prob. 10QCh. 11.5 - The National Collegiate Athletic Association has...
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- Let X1, .... Xn be a random sample from a population with location pdf f(x-Q). Show that the order statistics, T(X1, ...., Xn) = (X(1), ... X(n)) are a sufficient statistics for Q and no further reduction is possible?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_forwardConsider the following two formulations of the bivariate PRF, where ui and εi are both mean-0 stochastic disturbances (i.e random errors): yi = β0 + β1xi + u yi = α0 + α1(xi − x¯) + ϵ a) Write the OLS estimators of β1 and α1. Are the two estimators the same? b) What is the advantage, if any, of the second model over the first?arrow_forward
- Consider random variables Xand Y with following joint pdf given as f(x,y) ={x+y 0≤x≤1, 0≤y≤1, 0 elsewhere. Compute correlation coefficient, ρXYarrow_forwardFor a random variable (X) having pdf given by: f(x) = (k)x^3 where 0 ≤ x ≤ 1, compute the following: a) k b) E(X). c) Var(X). d) P(X > 0.25).arrow_forward
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