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Additional Statistical Techniques

  • Wallace R. Blischke
  • M. Rezaul Karim
  • D. N. Prabhakar Murthy
Chapter
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Abstract

In this chapter, we continue the discussion of basic statistical methods of importance in analysis of warranty data begun in  Chap. 9. Techniques discussed include parametric and nonparametric test for outliers; goodness-of-fit tests, including the ChiᾢSquare, KolmogoroffᾢSmirnov, and AndersonᾢDarling tests; tests for comparing means of two or more normal populations; basic linear regression and correlation analysis; estimation of functions of parameters, including the coefficient of variation, and cost and reliability functions; and tests of assumptions, including independence, normality, and equal population variances.

Keywords

Weibull Distribution Candidate Model System Reliability Asymptotic Variance Reliability Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Barnett V, Lewis T (1994) Outliers in statistical data. Wiley, New YorkMATHGoogle Scholar
  2. 2.
    Blischke WR, Murthy DNP (2000) Reliability. Wiley, New YorkMATHCrossRefGoogle Scholar
  3. 3.
    D’Agostino RB, Stephens MA (1986) Goodness-of-fit techniques. Dekker, New YorkMATHGoogle Scholar
  4. 4.
    Draper NR, Smith H (1998) Applied regression analysis, 3rd edn. Wiley-Interscience, New YorkMATHGoogle Scholar
  5. 5.
    Grubb FE (1969) Simple criteria for detecting outlying observations. Technometrics 1:1ᾢ24CrossRefGoogle Scholar
  6. 6.
    Høyland A, Rausand M (1994) System reliability theory. Wiley-Interscience, New YorkGoogle Scholar
  7. 7.
    Hulting FL, Robinson JA (1994) The reliability of a series system of repairable subsystems. Nav Res Logist Q 41:483ᾢ506MATHCrossRefGoogle Scholar
  8. 8.
    Kececioglu D (1994) Reliability engineering handbook, vol 2. Prentice-Hall, Englewood Cliffs, NJGoogle Scholar
  9. 9.
    Kapur KC, Lamberson LR (1977) Reliability in engineering design. Wiley, New YorkGoogle Scholar
  10. 10.
    Lawless JF (1982) Statistical models and methods for lifetime data. Wiley, New YorkMATHGoogle Scholar
  11. 11.
    Lorenzen TJ, Anderson VL (1993) Design of experiments. Marcel Dekker Inc., New YorkMATHGoogle Scholar
  12. 12.
    Martz HF, Waller RA (1982) Bayesian reliability analysis. Wiley, New YorkMATHGoogle Scholar
  13. 13.
    Martz HF, Waller RA (1990) Bayesian reliability analysis of complex series-parallel systems of binomial subsystems and components. Technometrics 32:407ᾢ416CrossRefGoogle Scholar
  14. 14.
    Martz HF, Waller RA, Fickas ET (1988) Bayesian reliability analysis of series systems of binomial subsystem s and components. Technometrics 30:143ᾢ159CrossRefGoogle Scholar
  15. 15.
    Montgomery DC (2005) Design and analysis of experiments, 6th edn. Wiley, New YorkMATHGoogle Scholar
  16. 16.
    Murthy DNP, Xie M, Jiang R (2004) Weibull models. Wiley, New YorkMATHGoogle Scholar
  17. 17.
    Spencer FW, Easterling RG (1986) Lower confidence bounds on system reliability using component data. Comm Statist Theory and Methods 18:4211ᾢ4227Google Scholar
  18. 18.
    Stuart A, Ord JK (1991) Kendall’s advanced theory of statistics, 5th edn, vol 2. Oxford University Press, New YorkMATHGoogle Scholar
  19. 19.
    Ury HK (1972) On distribution free confidence bounds for P(Y >X ). Technometrics 14:577ᾢ581MATHGoogle Scholar
  20. 20.
    Wackerly D, Mendenhall W, Scheaffer RL (2007) Mathematical statistics with applications. Duxbury, New YorkGoogle Scholar
  21. 21.
    Wu CFJ, Hamada M (2000) Experiments. Wiley Interscience, New YorkMATHGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Wallace R. Blischke
    • 1
  • M. Rezaul Karim
    • 2
  • D. N. Prabhakar Murthy
    • 3
  1. 1.Sherman Oaks, Los AngelesUSA
  2. 2.Department of StatisticsRajshahi UniversityRajshahiBangladesh
  3. 3.School of Mechanical and Mining EngineeringThe University of QueenslandBrisbaneAustralia

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