From the batch of goods, 2% was drawn at random without returning 400 items. Using theChebyshev inequality (*), estimate the probability that the number of failing elements among theselected elements will not exceed 5%.EX(*) P(X>e)<

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A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A random sample of 200 female high school students in India showed that 110 are on Facebook. A separate random sample of 150 male high school students in India showed that 69 are on Facebook. Let P1 and P2 be the proportion of all female and male high school students in India, respectively, who are on Facebook. Which the following are the estimate of p(combined), pc, and the standard test statistics, z, of the difference in the population proportions? O (C) pc = 0.51, z=pc = 0.51, z=(0.55 -0.46)-51/(0.51)(0.49)200+(0.51) (0.49)150 O pc = 0.11, z-(0.11 -0.51)-0V(0.51)(0.49)200+(0.51)(0.49)150 %3D O ic - 0.51, z-(0.55 -0.46)-0V(0.51)(0.49)200+(0.51)(0.49)150 %3D O ộc = 0.51, z-(0.55-0.46)-0v(0.46)(0.54)200+(0.55)(0.45)150 O Dc = 0.51, z-(0.55 -0.46)-0v(0.55)(0.45)200+(0.46) 54)150 Next STE 165 W
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The 2010 U.S. Census found the chance of a household being a certain size. The data is in the pmf below ("Households by age," 2013). Let X be the number (size) in a household. E(X) = k·P(X = k) 7 (or more) P(X=k) 0.267 0.336 0.158 0.137 0.063 0.024 0.015 k 1 2 3 5 6 a) The probability of a household size being more than 5, P(X > 5) = % b) In the long run, we are expected to see a household size of, E(X)= on average. Round answer to three decimal places. c) The probability that the size of a household is equal to two is %. d) The probability of a household size being three OR six is %.
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Benford's Law claims that numbers chosen from very large data files tend to have "1" as the first nonzero digit disproportionately often. In fact, research has shown that if you randomly draw a number from a very large data file, the probability of getting a number with "1" as the leading digit is about 0.301. Suppose you are an auditor for a very large corporation. The revenue report involves millions of numbers in a large computer file. Let us say you took a random sample of n = 250 numerical entries from the file and r = 60 of the entries had a first nonzero digit of 1. Let p represent the population proportion of all numbers in the corporate file that have a first nonzero digit of 1. Test the claim that p is less than 0.301 by using α = 0.01. What does the area of the sampling distribution corresponding to your P-value look like? a. The area in the right tail of the standard normal curve. b. The area not including the right tail of the standard normal curve.…
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From the batch of goods, 2% was drawn at random without returning 400 items. Using the Chebyshev inequality (*), estimate the probability that the number of failing elements among the selected elements will not exceed 5%. EX (*) P(X >e)<

From the batch of goods, 2% was drawn at random without returning 400 items. Using the Chebyshev inequality (), estimate the probability that the number of failing elements among the selected elements will not exceed 5%. EX () P(X >e)<