2016 Summer School in Statistics for Astronomers

2016年天文学家统计学暑期学校

• 批准号: 1613056
• 负责人: Gutti Babu
• 金额: $ 0.5万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-15 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1613056&HistoricalAwards=false
• 关键词: 2016; Summer; Statistics; Astronomers

2016 Summer School in Statistics for Astronomers; May 31-June 4 2016; Pennsylvania State University, University Park, State College, PAPenn State's very popular astrostatistics summer school has trained over 700 total participants since its inauguration in 2005. At this rate, they train about 10% of the nation's young astronomers. They give critical skills to the US scientific workforce. Highly skilled instructors provide an intense immersion in statistical methods. The courses are oriented towards graduate students and young researchers. The curriculum covers the underlying principles of modern statistics. It covers advanced methods useful in astronomy, and hands-on training in statistical software. Attendees gain much better expertise in statistics and its application to their science. They have a better understanding of how to teach this material to others. The value and meaning of statistics in science become clear. The instructors devote considerable effort to adapting the course material to their audience. In 2012, the course leaders published a formal textbook based on this curriculum, which continues to evolve.A vast range of statistical problems arises in modern astronomical and space sciences research, particularly due to the flood of data produced by ground-based and space-based surveys at many wavelengths. There has been a resurgence of interest in statistical and computational methods as researchers seek insight into the physical phenomena underlying such complex data. Common approaches either inadequately utilize known methods or require the invention of new methods. Regrettably, the statistical needs of physical scientists have been neglected in recent decades, even while modern statistical procedures implemented with computationally efficient algorithms became increasingly essential. Unfortunately, due to the structure of undergraduate and graduate curricula, U.S. astronomers are generally not well trained in statistical techniques. Statistics is an available technology that must be tapped to advance the needs of astronomy and astrophysics.The 2016 Summer School in statistical inference for young astronomers will present concepts and methodologies at an intermediate level, using experienced instructors and an innovative curriculum. Lectures are accompanied by hands-on software R tutorials, and training in high performance cluster computing with applications to astronomical datasets. The Penn State Research Computing & Cyberinfrastructure Group, and its Institute for CyberScience, are providing technical manpower and partially supporting the high-performance computing.

2016年天文学家统计学的暑期学校； 2016年5月31日至6月4日；自2005年就职以来，宾夕法尼亚州立大学，大学公园，州立大学，州立大学非常受欢迎的Astrostatistics Summer School培训了700多名参与者。以这种速度，他们培训了该国约10％的年轻天文学家。 他们为美国科学劳动力提供了关键的技能。 高技能的讲师对统计方法充满沉浸式。 这些课程针对研究生和年轻研究人员。 该课程涵盖了现代统计的基本原则。 它涵盖了对天文学有用的高级方法，以及统计软件中的动手培训。 与会者在统计数据及其对科学的应用方面获得了更好的专业知识。 他们对如何向他人教授这种材料有更好的了解。 统计在科学中的价值和含义变得清晰。 教练们付出了巨大的努力，将课程材料调整给听众。 2012年，该课程领导者根据该课程出版了一本正式的教科书，该课程继续发展。现代天文学和太空科学研究中出现了广泛的统计问题，特别是由于许多波长在基于地面的基于地面和空间的调查所产生的数据泛滥。 随着研究人员寻求对这种复杂数据的物理现象的洞察，人们对统计和计算方法的兴趣重新兴趣。 通用方法要么不充分地利用已知方法，要么需要发明新方法。 遗憾的是，近几十年来，物理科学家的统计需求被忽略了，即使使用计算有效算法实施的现代统计程序变得越来越重要。 不幸的是，由于本科和研究生课程的结构，美国天文学家通常没有接受统计技术的训练。 统计数据是一项可用的技术，必须采用以提高天文学和天体物理学的需求。2016年对年轻天文学家的统计推断的暑期学校将使用经验丰富的教师和创新的课程提出概念和方法。 讲座伴随着动手软件教程，并在高性能集群计算中进行培训，并应用于天文数据集的应用。 宾夕法尼亚州立研究计算与网络基础设施小组及其网络科学研究所正在提供技术人力，并部分支持高性能计算。