臺灣博碩士論文加值系統

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 鍵入論文的中文摘要
 In this study, we compare two approximate confidence interval estimators for the Bernoulliparameter \$p\$. The approximate confidence intervals are based on the normal and Poisson approximationsto binomial. The related tables and figures which are given here are helpful to indicate whichapproximation is more approriate. Besides, we also use the Greenwood's formula as a transformation tocompare its convergence to normality with that of arcsine transformation.
 Chapter 1 IntroductionChapter 2 Basic concepts and transformationChapter 3 Simulation and resultsChapter 4 Conclusions
 1. Blyth, C. R. (1986),``Approximate Binomial Confidence Limits,"Journal of the American Statistical Association, Vol. 81, p.843-855.2. Chen, H. (1990),`` The Accuracy of Approximate Intervals for a Binomial Parameter,"Journal of the American Statistical Association, Vol. 85, No. 410, p.514-518.3. Kalbfleisch, J. D., and Prentice, R. L.(1980),The Statistical Analysis of Failure Time Data,John Wiley And Sons.4. Lentner, C. (ed.)(1982), Giegy Scientific Tables(Vol. 2), Basel, Switzerland: Ciba-Geigy.5. Lehmann, E. L., and Loh, W. Y. (1990) ,`` Pointwise Versus Uniform Robustness of Some Large-Sample Tests and Confidence Intervals,"Scandinavian Journal of Statistics, 17 , p.177-187.6. Leemis, L. M., and Trivedi, K. S. (1996) ,`` A Comparison of Approximate Interval Estimators for the Bernoulli,"The American Statistician, Vol. 50, No. 1, p.63-68.7. Larsen, R. J., and Marx, M. L. (1986),An Introduction to Mathematical Statistics and Its Applications(2nd ed.),Englewood Cliffs, NJ: Prentice Hall.8. Trivedi, K. S. (1982), probability and Statistics with Reliability,Queuing and Computer Science Applications, Englewood Cliffs, NJ: Prentice-Hall.
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