원문정보
Interpretation of Quality Statistics Using Sampling Error
초록
영어
The research interprets the principles of sampling error design for quality statistics models such as hypothesis test, interval estimation, control charts and acceptance sampling. Introducing the proper discussions of the design of significance level according to the use of hypothesis test, then it presents two methods to interpret significance by Neyman-Pearson and Fisher. Second point of the study proposes the design of confidence level for interval estimation by Bayesian confidence set, frequentist confidential set and fiducial interval. Third, the content also indicates the design of type I error and type II error considering both productivity and customer claim for control chart. Finally, the study reflects the design of producer's risk with operating charistictics curve, screening and switch rules for the purpose of purchasing and subcontraction.
목차
1. 서론
2. 검정과 유의수준
2.1 검정의 용도
2.2 유의수준
2.3 P-Value
3. 추정과 신뢰수준
3.1 추정의 용도
3.2 신뢰수준
4. 관리도와 제1종 오차
4.1 관리도의 용도
4.2 제1종 오차
5. 샘플링 검사와 생산자 및 소비자 위험
5.1 샘플링 검사의 용도
5.2 생산지 위험과 소비자 위험
6. 결론
7. 참고문헌
