REU Sites: Summer Program Advancing Techniques in the Applied Learning of Statistics (SPATIAL-Stats)

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。位于华盛顿特区的美国大学的暑期项目推进统计学应用学习技术（SPATIAL-Stats）是一个为期8周的本科生暑期研究体验（REU）项目，邀请6名学生合作研究统计学和应用数学方面的问题。该课程旨在提高本科生对数学和统计的理解水平，并让他们参与创造性活动，从而使他们保持在数学和统计的管道中。学生将学习如何进行出版的科学研究，以及如何有效地将数学和统计研究传达给普通受众。该计划侧重于多样化的数学科学，以允许不同的观点和经验，以帮助解决世界问题。具体来说，该计划旨在通过加强学生的数学基础来解决代表性不足的数学和统计科学家的短缺问题，从而使他们在STEM领域有更高的抱负。研究目标将首先通过为学生提供为期三周的统计学和数学领域的密集讲座来实现，重点是计算机技能和理论基础。然后，学生们将在课程的剩余时间积极参与三个项目之一的研究，这些项目涵盖的主题包括赖尔登阵列、随机漫步和树，以及空间相关性对经验似然的影响。在暑期项目结束后，学生将继续接受指导，以支持他们在国家会议上的工作展示以及提交同行评审的期刊文章。学生们还将参加网络活动，与全国领先的研究人员见面。该计划将与暑期研究与学习计划（SPIRAL）一起进行，这些学生将一起参加到当地研究机构和行业的实地考察，以发现数学和统计研究的应用。参加空间统计的学生将与其他来自不同种族/民族背景的学生互动，以了解卓越和多样性在STEM中的重要性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The Summer Program Advancing Techniques in the Applied Learning of Statistics (SPATIAL-Stats) at American University, in Washington, DC is an 8-week summer Research Experience for Undergraduates (REU) program hosting 6 students to work collaboratively on research problems in statistics and applied mathematics. The program is designed to raise the level of mathematical and statistical understanding for undergraduate students and engage them in creative activities, thereby keeping them in the mathematics and statistics pipeline. Students will learn how to conduct scientific research for publication and how to effectively communicate mathematics and statistics research to a general audience. The program focuses on diversifying the mathematical sciences to allow for different views and experiences to help solve world problems. Specifically, the program aims to address the shortage of underrepresented mathematical and statistical scientists by strengthening students’ mathematical foundations to enable higher aspirations in STEM fields. The research goal will be accomplished first by providing students with intensive 3-week lectures in the fields of statistics and mathematics, focusing on both computer skills as well as theoretical foundations. The students will then spend the remainder of the program actively engaged in research on one of three projects which cover topics including Riordan Arrays, random walks and trees, and the effects of spatial correlation on empirical likelihood. Students will continue to be mentored after the conclusion of the summer program to support the presentation of their work at national conferences as well as submission of a peer-reviewed journal article. Students will also participate in networking activities to meet leading researchers across the country. The program will run in conjunction with the Summer Program in Research and Learning (SPIRAL), and together these students will participate in field trips to local research agencies and industry to discover applications of mathematical and statistical research. Students participating in SPATIAL-Stats will interact with other students with different racial/ethnic backgrounds with the intention of understanding the importance of excellence and diversity in STEM.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.