2016 Summer School in Statistics for Astronomers

2016天文学家统计学暑期学校；2016年5月31日至6月4日；宾夕法尼亚州立大学非常受欢迎的天文统计暑期学校自2005年成立以来，已经培训了700多名参与者。按照这个速度，他们培养了全国大约10%的年轻天文学家。他们为美国的科学工作者提供了关键技能。高技能的教师提供了一个密集的沉浸在统计方法。这些课程面向研究生和年轻的研究人员。课程包括现代统计学的基本原理。它涵盖了天文学中有用的先进方法，以及统计软件的实践培训。与会者在统计学及其应用方面获得了更好的专业知识。他们对如何把这些材料教给别人有了更好的理解。统计学在科学中的价值和意义变得清晰起来。教师们花了相当大的精力使课程材料适合他们的听众。2012年，课程负责人在此基础上出版了正式的教材，并不断完善。在现代天文和空间科学研究中出现了大量的统计问题，特别是由于在许多波长的地面和空间调查产生的大量数据。随着研究人员寻求深入了解这些复杂数据背后的物理现象，对统计和计算方法的兴趣已经重新抬头。普通方法要么不充分利用已知方法，要么需要发明新方法。遗憾的是，近几十年来，尽管现代统计程序的计算效率越来越高，但物理科学家的统计需求却被忽视了。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受过良好的统计技术训练。统计是一种可用的技术，必须加以利用，以促进天文学和天体物理学的需要。2016年面向青年天文学家的统计推断暑期学校将使用经验丰富的教师和创新的课程，介绍中级水平的概念和方法。讲座伴随着实际操作的软件R教程，以及应用于天文数据集的高性能集群计算的培训。宾夕法尼亚州立大学研究计算和网络基础设施组及其网络科学研究所提供技术人力并部分支持高性能计算。

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.