## Proceedings of the International School of Physics "Enrico Fermi", Volume 94 |

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Page 325

The size of an error is the probability that an element

the test case

easily detected if it has a large size since then it affects many input elements .

The size of an error is the probability that an element

**selected**from I according tothe test case

**selection**criterion results in failure due to that error . An error iseasily detected if it has a large size since then it affects many input elements .

Page 440

Maximum - likelihood estimator , Ô , for $ = 1 , for realizations # 1 , # 2 , # 3 , # 4 ,

for

slopes as the number of samples increases ) as the testing interval increases ...

Maximum - likelihood estimator , Ô , for $ = 1 , for realizations # 1 , # 2 , # 3 , # 4 ,

for

**selected**intervals , T . ( Straight lines added for continuity . ) ( with decreasingslopes as the number of samples increases ) as the testing interval increases ...

Page 475

distal sources proximal sources outcome activity appropriate strategy

novel condition training deficiency inexperienced operator definition /

procedure not followed premature commitment to strategy plant response ...

distal sources proximal sources outcome activity appropriate strategy

**selected**novel condition training deficiency inexperienced operator definition /

**selection**procedure not followed premature commitment to strategy plant response ...

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### Contents

STATISTICAL THEORY OF RELIABLITY | 8 |

Definitions and characterizations | 12 |

J KEILSON Stochastic models in reliability theory | 23 |

Copyright | |

37 other sections not shown

### Common terms and phrases

analysis application approach associated assume assumption BARLOW Bayesian calculation called complex components consider constant continuous correctness Course defined density depends derived described detected determine discussed distribution edited epochs equations equivalence ergodic errors estimate example exists expected exponential fact fail failure rate fault function given Hence important increasing independent input integration interest interval known likelihood limit Markov matrix mean measure method modules normal Note observed obtain occur operational parameters performance phase positive possible posterior predictive prior probability problem procedure prove random variables renewal repair requirements rule sample selected sequence simple software reliability space specification statistical stochastic structure Suppose task theorem theory tion transition tree University values York