Non-destructive evaluation. Non-destructive evaluation(NDE) describes methods that quantitatively characterize materials, tissues, and structures by non-invasive means, such as X-ray computed tomography, ultrasonic, and acoustic emission. Recently, NDE was used to detect defects in steel castings (JOM,May 2005). Assume that the probability that NDE detects a “hit” (i.e., predicts a defect in a steel casting) when, in fact, a defect exists is .97. (This is often called the probability of detection.) Also assume that the probability that NDE detects a hit when, in fact, no defect exists is .005. (This is called the probability of a false call.) Past experience has shown a defect occurs once in every 100 steel castings. If NDE detects a hit for a particular steel casting, what is the probability that an actual defect exists?

Short Answer

Expert verified

The required probability is 0.6621.

Step by step solution

01

Important formula

The Baye’s formula is

P(BiA)=P(BiA)P(A)=P(Bi)P(ABi)P(B1)P(ABi)+P(B2)P(AB2)+...+P(Bk)P(ABk)

02

The probability that an actual defect exists

Now,

Let A= defected, B=hit

PA=0.01PB\A=0.97PB\Ac=0.005PAc=1-PA=1-0.01=0.99

The probability that an actual defect exists given that NDE detects a hit particular steel casting is:

PA\B=PAPBAPAPBA+PAcPBAc=0.970.010.970.01+0.0050.99=0.6621

Therefore, the probability is 0.6621.

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Most popular questions from this chapter

Sanitarium administration of malaria cases. One of the most sedate health challenges in India is malaria. Accordingly, the Indian sanitarium director's must-have—the coffers to treat the high volume of admitted malaria cases. A study published in the National Journal of Community Medicine (Vol. 1, 2010) delved into whether the malaria admission rate is more advanced in months than in others. In a sample of 192 sanitarium cases admitted in January, 32 were treated for malaria.

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DEFECT*PRED_LOC crosstabulation


PRED_LOC
total
noyes

DEFECT False

True

total

440

29

429

49

20

69

449

49

498

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a. Describe the (approximate) sampling distribution of x under the assumption that H0 is true.

b. Describe the (approximate) sampling distribution of x under the assumption that the population mean is 70.

c. If m were really equal to 70, what is the probability that the hypothesis test would lead the investigator to commit a Type II error?

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The data is given below

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