In a notched tensile fatigue test on a titanium specimen, the expected number of cycles to first acoustic emission (used to indicate crack initiation) is u = 28,000, and the standard deviation of the number of cycles is o = 4000. Let X,, X, ...,X5 be a random sample of size 25, where each X, is the number of cycles on a different randomly selected specimen. Then the expected value of the sample mean v number of cycles until first emission is E(X) = µ = 28,000, and the expected total number of cycles for the specimens is E(T,) = nụ = 25(28,000) = 700,000. The standard deviations of X and T, are Vn = Vno = /25(4000) = If the sample size increases to n = 100, E(X) Is unchanged but o = 800 x , half of its previous value (the sample size must be quadrupled v to the ctandard devlation of
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![In a notched tensile fatigue test on a titanium specimen, the expected number of cycles to first acoustic emission (used to indicate crack initiation) isu =
the standard deviation of the number of cycles is o
28,000, and
4000. Let X,, X, . . . , X25 be a random sample of size 25, where each X; is the number of cycles on a different
Example 5.24
2'
randomly selected specimen. Then the expected value of the sample mean
number of cycles until first emission is E(X)
28,000, and the expected total
= U =
number of cycles for the
are
specimens is E(T,) = nµ = 25(28,000) = 700,000. The standard deviations of X and T,
ox = 0/Vn
V
V 25(4000) =
no =
If the sample size increases to n = 100, E(X) is unchanged but o ,
= 800
half of its previous value (the sample size must be quadrupled v
to
halve the standard deviation of X.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa0bb33da-4292-4a51-8799-113a66f1981e%2Fcedbdebf-fd27-4939-9f81-ee6e5b490ecc%2Fj995ovu_processed.png&w=3840&q=75)
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