Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
8th Edition
ISBN: 9781464158933
Author: David S. Moore, George P. McCabe, Bruce A. Craig
Publisher: W. H. Freeman
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Chapter 6.2, Problem 47UYK
(a)
To determine
Whether the value 30 is contained in the 95% confidence interval or not.
(b)
To determine
Whether the value 30 is contained in the 99% confidence interval or not.
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(c) Show that A is the limit of a decreasing sequence and A, is the limit of an
increasing sequence of sets.
3. Let A (-1, 1-1) for even n, and A, -(+) for odd n. Derive lim sup A,
and lim inf A
1. Let 2 (a, b, c} be the sample space.
the power sot of O
(c) Show that F= {0, 2, {a, b}, {b, c}, {b}} is not a σ-field. Add some elements
to make it a σ-field.
Chapter 6 Solutions
Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
Ch. 6.1 - Prob. 1UYKCh. 6.1 - Prob. 2UYKCh. 6.1 - Prob. 3UYKCh. 6.1 - Prob. 4UYKCh. 6.1 - Prob. 5UYKCh. 6.1 - Prob. 6UYKCh. 6.1 - Prob. 7UYKCh. 6.1 - Prob. 8UYKCh. 6.1 - Prob. 9UYKCh. 6.1 - Prob. 10UYK
Ch. 6.1 - Prob. 11UYKCh. 6.1 - Prob. 12ECh. 6.1 - Prob. 13ECh. 6.1 - Prob. 14ECh. 6.1 - Prob. 15ECh. 6.1 - Prob. 16ECh. 6.1 - Prob. 17ECh. 6.1 - Prob. 18ECh. 6.1 - Prob. 19ECh. 6.1 - Prob. 20ECh. 6.1 - Prob. 21ECh. 6.1 - Prob. 22ECh. 6.1 - Prob. 23ECh. 6.1 - Prob. 24ECh. 6.1 - Prob. 25ECh. 6.1 - Prob. 26ECh. 6.1 - Prob. 27ECh. 6.1 - Prob. 28ECh. 6.1 - Prob. 29ECh. 6.1 - Prob. 30ECh. 6.1 - Prob. 31ECh. 6.1 - Prob. 32ECh. 6.1 - Prob. 33ECh. 6.1 - Prob. 34ECh. 6.1 - Prob. 35ECh. 6.1 - Prob. 36ECh. 6.1 - Prob. 37ECh. 6.2 - Prob. 38UYKCh. 6.2 - Prob. 39UYKCh. 6.2 - Prob. 40UYKCh. 6.2 - Prob. 41UYKCh. 6.2 - Prob. 42UYKCh. 6.2 - Prob. 43UYKCh. 6.2 - Prob. 44UYKCh. 6.2 - Prob. 45UYKCh. 6.2 - Prob. 46UYKCh. 6.2 - Prob. 47UYKCh. 6.2 - Prob. 48UYKCh. 6.2 - Prob. 49UYKCh. 6.2 - Prob. 50UYKCh. 6.2 - Prob. 51UYKCh. 6.2 - Prob. 52ECh. 6.2 - Prob. 53ECh. 6.2 - Prob. 54ECh. 6.2 - Prob. 55ECh. 6.2 - Prob. 56ECh. 6.2 - Prob. 57ECh. 6.2 - Prob. 58ECh. 6.2 - Prob. 59ECh. 6.2 - Prob. 60ECh. 6.2 - Prob. 61ECh. 6.2 - Prob. 62ECh. 6.2 - Prob. 63ECh. 6.2 - Prob. 64ECh. 6.2 - Prob. 65ECh. 6.2 - Prob. 66ECh. 6.2 - Prob. 67ECh. 6.2 - Prob. 68ECh. 6.2 - Prob. 69ECh. 6.2 - Prob. 70ECh. 6.2 - Prob. 71ECh. 6.2 - Prob. 72ECh. 6.2 - Prob. 73ECh. 6.2 - Prob. 74ECh. 6.2 - Prob. 75ECh. 6.2 - Prob. 76ECh. 6.2 - Prob. 77ECh. 6.2 - Prob. 78ECh. 6.2 - Prob. 79ECh. 6.2 - Prob. 80ECh. 6.2 - Prob. 81ECh. 6.2 - Prob. 82ECh. 6.2 - Prob. 83ECh. 6.2 - Prob. 84ECh. 6.2 - Prob. 85ECh. 6.2 - Prob. 86ECh. 6.2 - Prob. 87ECh. 6.2 - Prob. 88ECh. 6.2 - Prob. 89ECh. 6.3 - Prob. 90UYKCh. 6.3 - Prob. 91UYKCh. 6.3 - Prob. 92ECh. 6.3 - Prob. 93ECh. 6.3 - Prob. 94ECh. 6.3 - Prob. 95ECh. 6.3 - Prob. 96ECh. 6.3 - Prob. 97ECh. 6.3 - Prob. 98ECh. 6.3 - Prob. 99ECh. 6.3 - Prob. 100ECh. 6.3 - Prob. 101ECh. 6.3 - Prob. 102ECh. 6.3 - Prob. 103ECh. 6.3 - Prob. 104ECh. 6.3 - Prob. 105ECh. 6.3 - Prob. 106ECh. 6.3 - Prob. 107ECh. 6.3 - Prob. 108ECh. 6.3 - Prob. 109ECh. 6.4 - Prob. 110ECh. 6.4 - Prob. 111ECh. 6.4 - Prob. 112ECh. 6.4 - Prob. 113ECh. 6.4 - Prob. 114ECh. 6.4 - Prob. 115ECh. 6.4 - Prob. 116ECh. 6.4 - Prob. 117ECh. 6.4 - Prob. 118ECh. 6.4 - Prob. 120ECh. 6.4 - Prob. 119ECh. 6.4 - Prob. 121ECh. 6 - Prob. 122ECh. 6 - Prob. 123ECh. 6 - Prob. 136ECh. 6 - Prob. 125ECh. 6 - Prob. 124ECh. 6 - Prob. 126ECh. 6 - Prob. 127ECh. 6 - Prob. 128ECh. 6 - Prob. 129ECh. 6 - Prob. 130ECh. 6 - Prob. 131ECh. 6 - Prob. 132ECh. 6 - Prob. 133ECh. 6 - Prob. 134ECh. 6 - Prob. 135ECh. 6 - Prob. 137ECh. 6 - Prob. 138ECh. 6 - Prob. 139ECh. 6 - Prob. 140E
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- 5. State without proof the uniqueness theorem of a probability function (arrow_forward2. (a) Define lim sup A,. Explain when an individual element of 2 lies in A* = lim sup A. Answer the same for A, = lim inf A,,.arrow_forward(c) Show that the intersection of any number of a-fields is a g-field. Redefine (A) using this fact.arrow_forward
- (b) For a given sequence A, of subsets of 92, explain when we say that A,, has a limit.arrow_forward1. Let 2 (a, b, c} be the sample space. (b) Construct a a-field containing A = {a, b} and B = {b, c}.arrow_forward2= 1. Let 2 {a, b, c} be the sample space. (a) Write down the power set of 2.arrow_forward
- 1. Let 2 (a, b, c)} be the sample space. (a) Write down the power set of 2. (b) Construct a σ-field containing A = {a, b} and B = {b, c}. (c) Show that F= {0, 2, {a, b}, {b, c}, {b}} is not a σ-field. Add some elements to make it a σ-field..arrow_forward13. Let (, F, P) be a probability space and X a function from 2 to R. Explain when X is a random variable.arrow_forward24. A factory produces items from two machines: Machine A and Machine B. Machine A produces 60% of the total items, while Machine B produces 40%. The probability that an item produced by Machine A is defective is P(DIA)=0.03. The probability that an item produced by Machine B is defective is P(D|B)=0.05. (a) What is the probability that a randomly selected product be defective, P(D)? (b) If a randomly selected item from the production line is defective, calculate the probability that it was produced by Machine A, P(A|D).arrow_forward
- (b) In various places in this module, data on the silver content of coins minted in the reign of the twelfth-century Byzantine king Manuel I Comnenus have been considered. The full dataset is in the Minitab file coins.mwx. The dataset includes, among others, the values of the silver content of nine coins from the first coinage (variable Coin1) and seven from the fourth coinage (variable Coin4) which was produced a number of years later. (For the purposes of this question, you can ignore the variables Coin2 and Coin3.) In particular, in Activity 8 and Exercise 2 of Computer Book B, it was argued that the silver contents in both the first and the fourth coinages can be assumed to be normally distributed. The question of interest is whether there were differences in the silver content of coins minted early and late in Manuel’s reign. You are about to investigate this question using a two-sample t-interval. (i) Using Minitab, find either the sample standard deviations of the two variables…arrow_forwardHomework Let X1, X2, Xn be a random sample from f(x;0) where f(x; 0) = (-), 0 < x < ∞,0 € R Using Basu's theorem, show that Y = min{X} and Z =Σ(XY) are indep. -arrow_forwardHomework Let X1, X2, Xn be a random sample from f(x; 0) where f(x; 0) = e−(2-0), 0 < x < ∞,0 € R Using Basu's theorem, show that Y = min{X} and Z =Σ(XY) are indep.arrow_forward
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