Investigation and Construction of Statistical Designs for Multifactorial Experiments

- 建议编号：DMS 9803596 PI： Samad Hedayat机构： 伊利诺伊大学芝加哥分校项目： 统计设计的研究与构建 多因子实验 摘要： 研究人员研究科学和工业实验的设计和分析领域的统计问题，其中结果受到多个因素和噪音的影响。目标是确定最佳因素组合，同时最大限度地减少和测量噪音。研究工作主要集中在能够调查位置和分散效应的设计，具有高强度的复合正交表，g-设计作为核心子设计，以及强度t+的正交表的构建。 任何严肃的科学研究的成功都取决于它的设计方式以及收集和分析的相关数据。噪音是最大的滋扰，而目标是将结果与影响研究的因素水平联系起来。几乎所有的社会、工程、环境和医学研究都是如此。完全消除噪音既费钱又不明智。事实上，在许多研究中，只要知道噪声的来源和强度就足够了。在后一种情况下，可以探索周围因素如何影响结果。研究人员探索所有这些相互关联的主题，并确定新的成本和时间效益和改进的统计设计，能够处理这些高度复杂的科学问题。

----------------------------------------------------------------------- Proposal Number: DMS 9803596 PI: Samad Hedayat Institution: University of Illinois at Chicago Project: Investigation and Construction of Statistical Designs for Multifactorial Experiments Abstract: The investigator studies statistical problems in the area of design and analyses of scientific and industrial experiments in which the outcomes are influenced by multiple factors and noise. The goal will be to identify the best factor combinations while minimizing and measuring the noise. The research effort is mainly concentrated in the construction of designs capable of investigating location and dispersion effects, compound orthogonal arrays with high strength, g-designs as core sub-designs ,and orthogonal arrays of strength t plus. The success of any serious scientific study depends on the way it is designed and the related data being collected and analyzed. Noise is the biggest nuisance while the goal is to relate the outcomes to the levels of the factors influencing the study. This is true in almost all social, engineering, environmental, and medical studies. It is costly and indeed unwise to eliminate noise entirely. Indeed in many studies it will be enough if one knows the source and the intensity of noise. Under the latter condition it is possible to explore how the surrounding factors are impacting the outcomes. The investigator explores all these interconnected topics and identifies new cost- and time-effective and improved statistical designs capable of handling these highly complicated scientific issues.