원문정보
Implementation of Statistical Significance and Practical Significance Using Research Hypothesis and Statistical Hypothesis in the Six Sigma Projects
초록
영어
This paper aims to propose a new steps of hypothesis testing using analysis process and improvement process in the six sigma DMAIC. The six sigma implementation models proposed in this paper consist of six steps. The first step is to establish a research hypothesis by specification directionality and FBP(Falsibility By Popper). The second step is to translate the research hypothesis such as RHAT(Research Hypothesis Absent Type) and RHPT(Research Hypothesis Present Type) into statistical hypothesis such as (Null Hypothesis) and (Alternative Hypothesis). The third step is to implement statistical hypothesis testing by PBC(Proof By Contradiction) and proper sample size. The fourth step is to interpret the result of statistical hypothesis test. The fifth step is to establish the best conditions of product and process conditions by experimental optimization and interval estimation. The sixth step is to draw a conclusion by considering practical significance and statistical significance. Important for both quality practitioners and academicians, case analysis on six sigma projects with implementation guidelines are provided.
목차
1. 서론
2. 연구가설과 통계가설의 설정방안
2.1 연구가설과 통계가설
2.2 식스시그마에서 가설설정 방안
3. 목표검정과 비목표검정의 적용방안
3.1 스펙과 목표성
3.2 DMAIC 단계별 목표검정
4. DMAIC 분석단계와 개선단계에서 샘플크기 적용방안
5. 식스시그마에서 가설검정의 6단계
6. 식스시그마 프로젝트에서오적용 및 이해
6.1 1-2단계의 연역적 과정에서의 오적용사례와 이해
6.2 3-6단계의 귀납적 과정에서의 오적용사례와 이해
7. 결론
8. 참고문헌