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2019 | OriginalPaper | Buchkapitel

19. Sampling Plans and Confidence Intervals

verfasst von : J. W. McPherson

Erschienen in: Reliability Physics and Engineering

Verlag: Springer International Publishing

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Abstract

Before purchasing a large number of devices, a customer will likely ask the supplier about the defect level for the product being offered. The customer’s reliability inquiry is often expressed as: what is the defect level for the population of such devices in terms of number of defective devices per hundred, number of defective devices per thousand, number of defective devices per million (dpm), etc.? To determine the fraction defective, a sample of the devices is randomly selected from the population and this sample is tested/stressed to determine the fraction defective. After the fraction defective is determined for the sample, then it is only natural to ask: based on the sample size used, what is the confidence interval for the population fraction defective? To answer this critically important question, we must understand the basics of sampling theory.

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Fußnoten
1
Generally, in sampling theory, we round up the sample size requirement.
 
2
The level of significance a is the probability that population x50 could be outside the range given by Eq. (19.21). The confidence level P is the probability that the population x50 will be within the range described by Eq. (19.21). Thus, P is the complement of a such that P + α = 1.
 
3
Note that this equation gives only single point estimation for the average failure rate over the interval t. It does not tell us whether the failure rate is increasing, decreasing, or remains constant. To determine this, several sequential periods of time would have to be studied.
 
Literatur
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Metadaten
Titel
Sampling Plans and Confidence Intervals
verfasst von
J. W. McPherson
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-319-93683-3_19

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