Example 6-24. Use the relation E(AXª+BX'+CX°)² >0, X being a random variable with E(X) = 0, E denoting the mathematical expectation, to show that Hatb Hate Matb H2b Hotc 20, Hn denoting the nth moment about mean. ... Hate Ho+c Hence or otherwise show that Pearson Beta-coefficients satisfy the inequality B2 – B1 – 1 20. Also deduce that B22 1.
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- Suppose X1, X2, ... , Xn is a random sample and Xi = {1, with probability p 0, with probability 1-p} for every i = 1, 2, ... , n. Find the Moment Generating Function of ∑i=1n Xi . What is the distribution of ∑i=1n Xi ?A k out of n system is one in which there is a group of n components, and the system will function if at least k of the components function. Assume the components function independently of one another. a) In a 3 out of 5 system, each component has probability 0.9 of functioning. What is the probability that the system will function? b) In a 3 out of n system, in which each component has probability 0.9 of functioning, what is the smallest value of n needed so that the probability that the system functions is at least 0.90?Consider a random sample X1,...,Xn,... ∼ iid Beta(θ,1) for n > 2. Prove that the MLE and UMVUE are both consistent estimators for θI got MLE = n/-∑logXi and UMVUE = (n-1)/∑logXi. Need help in proving consistency
- Each of 14 refrigerators of a certain type has been returned to a distributor because of an audible, high-pitched, oscillating noise when the refrigerators are running. Suppose that 9 of these refrigerators have a defective compressor and the other 5 have less serious problems. If the refrigerators are examined in random order, let X be the number among the first 6 examined that have a defective compressor. (I have figured out part "a" but need help with "b" and P(X ≤ 3) in "c") (a) Calculate P(X = 4) and P(X ≤ 4). (Round your answers to four decimal places.) P(X = 4) = P(X ≤ 4) = (b) Determine the probability that X exceeds its mean value by more than 1 standard deviation. (Round your answer to four decimal places.) (c) Consider a large shipment of 400 refrigerators, of which 40 have defective compressors. If X is the number among 25 randomly selected refrigerators that have defective compressors, describe a less tedious way to calculate (at least approximately)…Let X1, X2, ... , Xn be a random sample from N(μ, σ2). Find the Moment Generating Function of X̅. If n = 16 and σ = 2, compute P(-1 ≤ X̅ - μ ≤ 1).1- The number of items produced in a factory during a week is known to be a randomvariable with mean 50● Using Markov's inequality, what can you say about the probability that this week'sproduction exceeds 75?● If the variance of one week's production is equal to 25, then using Chebyshev'sinequality, what can be said about the probability that this week's production isbetween 40 and 60?
- If X1, X2, ... , Xn constitute a random sample of size n from an exponential population, show that X is a consis-tent estimator of the parameter θ.A study to compare two insurance companies on length of stay for pediatric asthma patients randomly sampled 393 cases from Insurer A. An independent random sample of 396 cases from Insurer B gave the results on length of stay, and the summary statistics are show below. Insurer A (Group 1): x⎯⎯⎯x¯ = 2.31, ss = 1.22, nn = 393Insurer B (Group 2): x⎯⎯⎯x¯ = 2.96, ss = 1.5, nn = 396 Unless otherwise stated, give your answers to three decimal places. Construct a 99% confidence interval for the difference in average length of stay between Insurer A and Insurer B. Give your answers to three decimal places. Use t∗=2.582t∗=2.582.( , ) Conduct a hypothesis test to determine whether the average length of stay for Insurer A is different from than the average length of stay for Insurer B. What is the parameter of interest?i. ppii. μμiii. p1−p2p1−p2iv. μ1−μ2μ1−μ2v. μdμd What is the correct null value for this test? What sign should appear in the alternative hypothesis?i. == ii.…If X1, X2, and X3 constitute a random sample of sizen = 3 from a Bernoulli population, show that Y =X1 + 2X2 + X3 is not a sufficient estimator of θ. (Hint:Consider special values of X1, X2, and X3.)
- Suppose that there are two identically-looking batteries in a box. The first one should last for a time that is exponentially distributed with parameter λ1 = 1 (in months). The second one should last for a time that is exponentially distributed with parameter λ2 = 2. A battery has been picked randomly and is still working after two months. Given this information, what is the probability that the first battery was picked?A certain company produces fidget spinners with ball bearings made of either plastic or metal. Under standard testing conditions, fidget spinners from this company with plastic bearings spin for an average of 2.7 minutes, while those from this company with metal bearings spin for an average of 4.2 minutes. A random sample of three fidget spinners with plastic bearings is selected from company stock, and each is spun one time under the same standard conditions; let x¯1x¯1 represent the average spinning time for these three spinners. A random sample of seven fidget spinners with metal bearings is selected from company stock, and each is likewise spun one time under standard conditions; let x¯2x¯2 represent the average spinning time for these seven spinners. What is the mean μ(x¯1−x¯2)μ(x¯1−x¯2) of the sampling distribution of the difference in sample means x¯1−x¯2x¯1−x¯2 ? 3(2.7)−7(4.2)=−21.33(2.7)−7(4.2)=−21.3 A 3−7=−43−7=−4 B 2.7−4.2=−1.52.7−4.2=−1.5 C…Workers at a large toxic cleanup project are concerned that their white blood cell counts may have been reduced. Let x be a random variable that represents white blood cell count per cubic millimeter of whole blood in a healthy adult. Then μ = 7500 andσ ≈ 1750.† A random sample ofn = 70 workersfrom the toxic cleanup site were given a blood test that showedx = 6920.What is the probability that, for healthy adults,xwill be this low or lower?(a) How does the central limit theorem apply? Explain. The central limit theorem describes the distribution of x as normal with mean μ x = 7500 and σ x≈1750.0.The central limit theorem describes the distribution of x as normal with mean μ x = 7500 and σ x≈209.2. The central limit theorem does not apply because the sample size is too small.The central limit theorem describes the distribution of x as normal with mean μ x = 7500 and σ x≈25.0. (b) ComputeP(x ≤ 6920).(Round your answer to four decimal places.) P(x ≤ 6920)= (c) Based on your answer to…