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Planning Experiments with Causal Graphs
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Planning Experiments with Causal Graphs. |
| 개인저자 | Matiasz, Nicholas John. |
| 단체저자명 | University of California, Los Angeles. Bioengineering. |
| 발행사항 | [S.l.]: University of California, Los Angeles., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 123 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-10A(E). Dissertation Abstract International |
| ISBN | 9780438016101 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Los Angeles, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: A.
Advisers: Alex A T Bui |
| 요약 | Scientists aim to design experiments and analyze evidence to obtain maximum knowledge. Although scientists have many statistical methods to guide how they analyze evidence, they have relatively few methods to quantify the convergence of evidence |
| 요약 | This dissertation shows how scientific results can be merged to yield new inferences by determining whether the results are consistent with various causal structures. Also presented is a Bayesian model of scientific consensus building, based on |
| 일반주제명 | Information science. Biology. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
