2016 Summer School in Statistics for Astronomers

2016年天文学家统计暑期学校；2016年5月31日至6月4日；宾夕法尼亚州立大学、大学公园、州立学院、帕彭州非常受欢迎的天体统计暑期学校自2005年开办以来，共培训了700多名参与者。按照这个速度，他们培养了这个国家大约10%的年轻天文学家。他们为美国的科学工作者提供关键技能。高技能的讲师提供了对统计方法的强烈沉浸。这些课程面向研究生和年轻的研究人员。该课程涵盖了现代统计学的基本原理。它涵盖了在天文学中有用的先进方法，以及统计软件方面的实践培训。与会者在统计学及其在他们的科学中的应用方面获得了更好的专业知识。他们更好地理解如何将这些材料传授给其他人。统计学在科学中的价值和意义变得清晰起来。讲师们花了相当大的精力来调整课程材料以适应他们的听众。2012年，课程负责人出版了一本基于这一课程的正式教科书，该课程还在继续发展。现代天文学和空间科学研究中出现了大量统计问题，特别是由于许多波长的地面和空间调查产生了大量数据。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，人们对统计和计算方法的兴趣重新抬头。常见的方法要么没有充分利用已知的方法，要么需要发明新的方法。令人遗憾的是，近几十年来，物理学家的统计需求被忽视了，即使用计算效率高的算法实施的现代统计程序变得越来越重要。不幸的是，由于本科生和研究生课程的结构，美国天文学家通常在统计技术方面没有得到很好的培训。统计学是一种可用的技术，必须利用它来推动天文学和天体物理学的需求。2016年年轻天文学家统计推断暑期学校将使用经验丰富的教师和创新的课程，在中级水平上介绍概念和方法。授课内容包括实际操作的软件R教程，以及高性能集群计算和天文数据集应用方面的培训。宾夕法尼亚州立大学研究计算和网络基础设施集团及其网络科学研究所正在提供技术人力，并在一定程度上支持高性能计算。

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.