With a = 7, MC Monte Carlo, CLT = Central Limit Theorem
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With a = 7: This means that we have a constant value of 7 that we will be working with. Show more…
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The central limit theorem (CLT) is considered to be an important result in statistics because a. the CLT allows us to estimate the population mean without knowing the exact form of the population distribution, provided n is reasonably large. b. the CLT allows us to assume that the population distribution is approximately normal, provided n is reasonably large. c. the CLT allows us to construct confidence intervals for the population mean without knowing the exact form of the population distribution, provided n is reasonably large. d. All of these choices are correct.
Madhur L.
The central limit theorem can be used to analyze round-off error. Suppose that the round-off error is represented as a uniform random variable on [-1,1]. (i) Suppose 100 numbers are added. Use the CLT to approximate the probability that the total round-off error exceeds 7 in absolute value (that is, greater than 7 or less than -7). (ii) Suppose 100 numbers are added. Use Chebyshev's inequality to obtain an upper bound on the probability that the total round-off error exceeds 7 in absolute value. (iii) Which is closer to the true probability, the approximation in part (i) or the upper bound in part (ii)? Explain.
Write out the content of central limit theorem (CLT). Then use CLT to discuss the relationship of Bernoulli distribution, Binomial distribution and Normal distribution.
Adi S.
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